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A

abortExperiment() - Method in class milk.experiment.MIRemoteExperiment: Set the abort flag
acceptResult(MIResultProducer, Object[], Object[]) - Method in interface milk.experiment.MIResultListener: Accepts results from a ResultProducer.
acceptResult(MIResultProducer, Object[], Object[]) - Method in class milk.experiment.MIInstancesResultListener: Collects each instance and adjusts the header information.
acceptResult(MIResultProducer, Object[], Object[]) - Method in class milk.experiment.MIDatabaseResultListener: Submit the result to the appropriate table of the database
acceptResult(MIResultProducer, Object[], Object[]) - Method in class milk.experiment.MICSVResultListener: Just prints out each result as it is received.
actionPerformed(ActionEvent) - Method in class milk.gui.experiment.MIRunPanel: Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class milk.gui.experiment.MIHostListPanel: Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class milk.gui.experiment.MIDatasetListPanel: Handle actions when buttons get pressed.
add(Exemplar) - Method in class milk.core.Exemplars: Adds one exemplar to the exemplars
add(Instance) - Method in class milk.core.Exemplars: Adds one instance to one of the exemplars
add(Instance) - Method in class milk.core.Exemplar: Adds one instance to the end of the set.
addActionListener(ActionListener) - Method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Add a listener interested in kowing about editor status changes
addCheckBoxActionListener(ActionListener) - Method in class milk.gui.experiment.MIDistributeExperimentPanel: Enable objects to listen for changes to the check box
addPropertyChangeListener(PropertyChangeListener) - Method in class milk.gui.experiment.MISetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.SelectPanel: Add the property change listener to hear the change of "addedExs" property of this class.
addPropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.MIPanel: Add the property change listener to hear the change of color and "exemplars" property of this class.
addPropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.GeomPanel: Add the property change listener to hear the change of "XAxis" and "YAxis" property of this class.
addPropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.DistributionPanel: Add the property change listener to hear the change of "XAxis" and "SD" property of this class.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class milk.experiment.MIRemoteExperiment: Add an object to the list of those interested in recieving update information from the MIRemoteExperiment
addRemoteHost(String) - Method in class milk.experiment.MIRemoteExperiment: Add a host name to the list of remote hosts
advanceCounters() - Method in class milk.experiment.MIRemoteExperiment: overides the one in Experiment
advanceCounters() - Method in class milk.experiment.MIExperiment: Increments iteration counters appropriately.
arrayToString(Object[]) - Static method in class milk.experiment.MIDatabaseUtils: Converts an array of objects to a string by inserting a space between each element.
attribute(int) - Method in class milk.core.Exemplars: Returns an attribute.
attribute(String) - Method in class milk.core.Exemplars: Returns an attribute given its name.
AVAILABLE - Static variable in class milk.experiment.MIRemoteExperiment
availableHost(int) - Method in class milk.experiment.MIRemoteExperiment: Pushes a host back onto the queue of available hosts and attempts to launch a waiting experiment (if any).
avgCost() - Method in class milk.classifiers.MIEvaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
Axis - class milk.visualize.Axis.: Helper class standing for the axis values and index.
Axis() - Constructor for class milk.visualize.Axis

B

BagStats - class milk.data.BagStats.
BagStats() - Constructor for class milk.data.BagStats
buildClassifier(Exemplars) - Method in class milk.classifiers.TLDSimple
buildClassifier(Exemplars) - Method in class milk.classifiers.TLD
buildClassifier(Exemplars) - Method in class milk.classifiers.SimpleMI: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MIWrapper: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MIRBFNetwork: Builds the classifier.
buildClassifier(Exemplars) - Method in class milk.classifiers.MINND: As normal Nearest Neighbour algorithm does, it's lazy and simply records the exemplar information (i.e.
buildClassifier(Exemplars) - Method in class milk.classifiers.MILRGEOM: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MILRARITH: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MILR: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MIClassifier: Generates a classifier.
buildClassifier(Exemplars) - Method in class milk.classifiers.MIBoost: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.MDD: Builds the classifier
buildClassifier(Exemplars) - Method in class milk.classifiers.DD: Builds the classifier

C

cacheKeyNameTipText() - Method in class milk.experiment.MIDatabaseResultListener: Returns the tip text for this property
change - Variable in class milk.visualize.MIPanel
checkForStringAttributes() - Method in class milk.core.Exemplars: Checks for string attributes in the Exemplars
checkInstance(Instance) - Method in class milk.core.Exemplar: Checks if the given instance is compatible with this Exemplar.
clas - Variable in class milk.visualize.MIPanel
classAttribute() - Method in class milk.core.Exemplars: Returns the class attribute.
classAttribute() - Method in class milk.core.Exemplar: Returns the class attribute.
classFirst(boolean) - Method in class milk.experiment.MIExperiment: Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classifierTipText() - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns the tip text for this property
classifyExemplar(Exemplar) - Method in class milk.classifiers.TLDSimple
classifyExemplar(Exemplar) - Method in class milk.classifiers.TLD
classifyExemplar(Exemplar) - Method in class milk.classifiers.SimpleMI: Computes the distribution for a given exemplar
classifyExemplar(Exemplar) - Method in class milk.classifiers.MINND: Use Kullback Leibler distance to find the nearest neighbours of the given exemplar.
classifyExemplar(Exemplar) - Method in class milk.classifiers.MIClassifier: Classifies the given test instance.
classIndex - Variable in class milk.visualize.MIPanel
classIndex() - Method in class milk.core.Exemplars: Returns the class attribute's index.
classIndex() - Method in class milk.core.Exemplar: Returns the class attribute's index.
classValue() - Method in class milk.core.Exemplar: Returns the class value of this exemplar.
cleanse(Exemplar) - Method in class milk.classifiers.MINND: Cleanse the given exemplar according to the valid and noise data statistics
colorList - Variable in class milk.visualize.PlotPanel: The list of the colors used
colorList - Variable in class milk.visualize.MIPanel
compactify() - Method in class milk.core.Exemplars: Compactifies each exemplar in this Exemplars
compactify() - Method in class milk.core.Exemplar: Compactifies the set of instances in this exemplar
confusionMatrix() - Method in class milk.classifiers.MIEvaluation: Returns a copy of the confusion matrix.
CONNECTION_FAILED - Static variable in class milk.experiment.MIRemoteExperiment
connectToDatabase() - Method in class milk.experiment.MIDatabaseUtils: Opens a connection to the database
contentsChanged(ListDataEvent) - Method in class milk.visualize.SelectPanel
convertToAttribX(double) - Method in class milk.visualize.PlotPanel: convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class milk.visualize.PlotPanel: convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class milk.visualize.PlotPanel: Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class milk.visualize.PlotPanel: Convert an raw y value to Panel y coordinate.
convertToRelativePath(File) - Method in class milk.gui.experiment.MIDatasetListPanel: Converts a File's absolute path to a path relative to the user (ie start) directory
correct() - Method in class milk.classifiers.MIEvaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
cp - Variable in class milk.visualize.MIPanel
createEx(int, double[][], RandomVariates) - Static method in class milk.data.TLDSimpleData
createEx(int, double[][], RandomVariates) - Static method in class milk.data.TLDData
createExperimentIndex() - Method in class milk.experiment.MIDatabaseUtils: Attempts to create the experiment index table
createExperimentIndexEntry(MIResultProducer) - Method in class milk.experiment.MIDatabaseUtils: Attempts to insert a results entry for the table into the experiment index.
createResultsTable(MIResultProducer, String) - Method in class milk.experiment.MIDatabaseUtils: Creates a results table for the supplied result producer.
crossValidateModel(MIClassifier, Exemplars, int) - Method in class milk.classifiers.MIEvaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of exemplars.
crossValidateModel(String, Exemplars, int, String[]) - Method in class milk.classifiers.MIEvaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of exemplars.

D

databaseURLTipText() - Method in class milk.experiment.MIDatabaseUtils: Returns the tip text for this property
DATASET_FIELD_NAME - Static variable in class milk.experiment.MIRandomSplitResultProducer
DATASET_FIELD_NAME - Static variable in class milk.experiment.MICrossValidationResultProducer
DD - class milk.classifiers.DD.: Re-implement the Diverse Density algorithm, changes the testing procedure.
DD() - Constructor for class milk.classifiers.DD
delete() - Method in class milk.core.Exemplars: Removes all Exemplars from the set.
delete(int) - Method in class milk.core.Exemplars: Removes an exemplar at the given position from the set.
deleteAttributeAt(int) - Method in class milk.core.Exemplars: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class milk.core.Exemplar: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteStringAttributes() - Method in class milk.core.Exemplars: Deletes all string attributes in the dataset.
deleteWithMissing(Attribute) - Method in class milk.core.Exemplars: Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(int) - Method in class milk.core.Exemplars: Removes all instances with missing values for a particular attribute from the dataset.
determineColumnConstraints(MIResultProducer) - Method in interface milk.experiment.MIResultListener: Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
determineColumnConstraints(MIResultProducer) - Method in class milk.experiment.MIDatabaseResultListener: Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
determineColumnConstraints(MIResultProducer) - Method in class milk.experiment.MICSVResultListener: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
disconnectFromDatabase() - Method in class milk.experiment.MIDatabaseUtils: Closes the connection to the database.
distributedExperimentSelected() - Method in class milk.gui.experiment.MIDistributeExperimentPanel: Returns true if the distribute experiment checkbox is selected
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MIWrapper: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MIRBFNetwork: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MILRGEOM: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MILRARITH: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MILR: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MIClassifier: Predicts the class memberships for a given exemplar.
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MIBoost: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.MDD: Computes the distribution for a given exemplar
distributionForExemplar(Exemplar) - Method in class milk.classifiers.DD: Computes the distribution for a given exemplar
DistributionPanel - class milk.visualize.DistributionPanel.: This class implements a panel that allows user to select some exemplars to show their distributions
DistributionPanel() - Constructor for class milk.visualize.DistributionPanel: Constructor: besides the ones in MIPanel, it has two more comboxes for obtaining the x axis and the std.
divBy100(double) - Static method in class milk.classifiers.DD
doRun(int) - Method in interface milk.experiment.MIResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class milk.experiment.MICrossValidationResultProducer: Gets the results for a specified run number.
doRunKeys(int) - Method in interface milk.experiment.MIResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class milk.experiment.MICrossValidationResultProducer: Gets the keys for a specified run number.
DRIVERS - Static variable in class milk.experiment.MIDatabaseUtils: Holds the jdbc drivers to be used (only to stop them being gc'ed)

E

enumerateAttributes() - Method in class milk.core.Exemplars: Returns an enumeration of all the attributes.
enumerateAttributes() - Method in class milk.core.Exemplar: Returns an enumeration of all the attributes.
enumerateMeasures() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class milk.experiment.MICrossValidationResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
errorRate() - Method in class milk.classifiers.MIEvaluation: Returns the estimated error rate or the root mean squared error (if the class is numeric).
evaluateModel(MIClassifier, Exemplars) - Method in class milk.classifiers.MIEvaluation: Evaluates the classifier on a given set of exemplars.
evaluateModel(MIClassifier, String[]) - Static method in class milk.classifiers.MIEvaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(String, String[]) - Static method in class milk.classifiers.MIEvaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModelOnce(MIClassifier, Exemplar) - Method in class milk.classifiers.MIEvaluation: Evaluates the classifier on a single exemplar.
execute() - Method in class milk.experiment.MIRemoteExperimentSubTask: Run the experiment
execute(String) - Method in class milk.experiment.MIDatabaseUtils: Executes a SQL query.
Exemplar - class milk.core.Exemplar.: Class for handling an ordered set of weighted exemplars.
Exemplar(Exemplar) - Constructor for class milk.core.Exemplar: Constructor to form an exemplar by copying from another exemplar
Exemplar(Exemplar, int) - Constructor for class milk.core.Exemplar: Constructor creating an empty Exemplar with the same structure of the given exemplar and the given size
Exemplar(Instance, int) - Constructor for class milk.core.Exemplar: Constructor using one instance to form an exemplar
Exemplar(Instances) - Constructor for class milk.core.Exemplar: Constructor copying all instances and references to the header information from the given set of instances.
Exemplar(Instances, int) - Constructor for class milk.core.Exemplar: Constructor creating an exemplar with the given dataset and the given ID index
exemplar(int) - Method in class milk.core.Exemplars: Returns the exemplar at the given position.
exemplarPosterior(double[][], double[], Random, int[]) - Method in class milk.data.MIDataSample
exemplarPosterior(double[], double[]) - Method in class milk.data.MIDataPopulation
exemplars - Variable in class milk.visualize.MIPanel
Exemplars - class milk.core.Exemplars.: The class of a set of exemplars
Exemplars(Exemplars) - Constructor for class milk.core.Exemplars: Constructor to form an Exemplars by deep copying from another Exemplars
Exemplars(Exemplars, int) - Constructor for class milk.core.Exemplars: Constructor creating an empty Exemplars with the same structure of the given Exemplars and the given size (i.e.
Exemplars(Exemplars, int, int) - Constructor for class milk.core.Exemplars: Creates a new set of instances by copying a subset of another set.
Exemplars(Instances) - Constructor for class milk.core.Exemplars: Constructor using the given dataset and set ID index to 0
Exemplars(Instances, int) - Constructor for class milk.core.Exemplars: Constructor using the given dataset and set ID index to the given ID index.
EXP_INDEX_TABLE - Static variable in class milk.experiment.MIDatabaseUtils: The name of the table containing the index to experiments
EXP_RESULT_COL - Static variable in class milk.experiment.MIDatabaseUtils: The name of the column containing the results table name
EXP_RESULT_PREFIX - Static variable in class milk.experiment.MIDatabaseUtils: The prefix for result table names
EXP_SETUP_COL - Static variable in class milk.experiment.MIDatabaseUtils: The name of the column containing the experiment setup (parameters)
EXP_TYPE_COL - Static variable in class milk.experiment.MIDatabaseUtils: The name of the column containing the experiment type (ResultProducer)
experimentIndexExists() - Method in class milk.experiment.MIDatabaseUtils: Returns true if the experiment index exists.

F

falseNegativeRate(int) - Method in class milk.classifiers.MIEvaluation: Calculate the false negative rate with respect to a particular class.
falsePositiveRate(int) - Method in class milk.classifiers.MIEvaluation: Calculate the false positive rate with respect to a particular class.
FILE_EXTENSION - Static variable in class milk.experiment.MIExperiment: The filename extension that should be used for experiment files
findWeights(int, double[][]) - Method in class milk.classifiers.MINND: Use gradient descent to distort the MU parameter for the exemplar.
firstExemplar() - Method in class milk.core.Exemplars: Returns the first exemplar in the set.
fMeasure(int) - Method in class milk.classifiers.MIEvaluation: Calculate the F-Measure with respect to a particular class.
FOLD_FIELD_NAME - Static variable in class milk.experiment.MICrossValidationResultProducer
forName(String, String[]) - Static method in class milk.classifiers.MIClassifier: Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.

G

generateData(String[]) - Method in class milk.data.MIDataSample
generateData(String[]) - Method in class milk.data.MIDataPopulation
GeomPanel - class milk.visualize.GeomPanel.: This class implements a panel that allows user to select some exemplars to show their geometric distribution in 2D space
GeomPanel() - Constructor for class milk.visualize.GeomPanel: Constructor: besides the ones in MIPanel, it has two more comboxes for obtaining the x and y axes It also sets up SelectPanel and plot space
getAddedExs() - Method in class milk.visualize.SelectPanel
getAdvanceDataSetFirst() - Method in class milk.experiment.MIExperiment: Get the value of m_DataSetFirstFirst.
getBaseExperiment() - Method in class milk.experiment.MIRemoteExperiment: Get the base experiment used by this remote experiment
getCacheKeyName() - Method in class milk.experiment.MIDatabaseResultListener: Get the value of CacheKeyName.
getClassForIRStatistics() - Method in class milk.experiment.MIClassifierSplitEvaluator: Get the value of ClassForIRStatistics.
getClassifier() - Method in class milk.classifiers.MIWrapper: Get the classifier used as the classifier
getClassifier() - Method in class milk.classifiers.MIBoost: Get the classifier used as the classifier
getClassifier() - Method in class milk.experiment.MIClassifierSplitEvaluator: Get the value of Classifier.
getCompatibilityState() - Method in interface milk.experiment.MIResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a MIResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class milk.experiment.MICrossValidationResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCurrentDatasetNumber() - Method in class milk.experiment.MIExperiment: When an experiment is running, this returns the current dataset number.
getCurrentPropertyNumber() - Method in class milk.experiment.MIExperiment: When an experiment is running, this returns the index of the current custom property value.
getCurrentRunNumber() - Method in class milk.experiment.MIExperiment: When an experiment is running, this returns the current run number.
getDatabaseURL() - Method in class milk.experiment.MIDatabaseUtils: Get the value of DatabaseURL.
getDatasets() - Method in class milk.experiment.MIExperiment: Gets the datasets in the experiment.
getDebug() - Method in class milk.classifiers.MIWrapper: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.MILRGEOM: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.MILRARITH: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.MILR: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.MIBoost: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.MDD: Gets whether debugging output will be printed.
getDebug() - Method in class milk.classifiers.DD: Gets whether debugging output will be printed.
getDiscretizeBin() - Method in class milk.classifiers.MIBoost: Get the number of bins in discretization
getEditorActive() - Method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Returns true if the editor is currently in an active status---that is the array is active and able to be edited.
getExemplars() - Method in class milk.core.Exemplars: Returns a vector of exemplars in this Exemplars.
getExemplars() - Method in class milk.visualize.MIPanel: Functions provided only for bean box
getExperiment() - Method in class milk.experiment.MIRemoteExperimentSubTask: Get the experiment for this sub task
getExperiment() - Method in class milk.gui.experiment.MISetupPanel: Gets the currently configured experiment.
getFilesRecursively(File, Vector) - Method in class milk.gui.experiment.MIDatasetListPanel: Gets all the files in the given directory that match the currently selected extension.
getInstances() - Method in class milk.core.Exemplar: Returns the dataset in this exemplar
getKey() - Method in interface milk.experiment.MISplitEvaluator: Gets the key describing the current MISplitEvaluator.
getKey() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the key describing the current SplitEvaluator.
getKeyNames() - Method in interface milk.experiment.MISplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in interface milk.experiment.MIResultProducer: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class milk.experiment.MICrossValidationResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeyTypes() - Method in interface milk.experiment.MISplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in interface milk.experiment.MIResultProducer: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class milk.experiment.MICrossValidationResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getLower() - Method in class milk.gui.experiment.MIRunNumberPanel: Gets the current lower run number.
getMaxIterations() - Method in class milk.classifiers.MIBoost: Get the maximum number of boost iterations
getMaxY() - Method in class milk.visualize.PlotPanel: Return the current max value of the attribute plotted on the y axis, i.e.
getMeasure(String) - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class milk.experiment.MICrossValidationResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns the value of the named measure
getMethod() - Method in class milk.classifiers.MIWrapper: Get the method used in testing.
getNotes() - Method in class milk.experiment.MIExperiment: Get the user notes.
getNumClusters() - Method in class milk.classifiers.MIRBFNetwork: Get the Num_clusters value.
getNumFolds() - Method in class milk.experiment.MICrossValidationResultProducer: Get the value of NumFolds.
getOptions() - Method in class milk.classifiers.TLDSimple: Gets the current settings of the Classifier.
getOptions() - Method in class milk.classifiers.TLD: Gets the current settings of the Classifier.
getOptions() - Method in class milk.classifiers.SimpleMI: Gets the current settings of the Classifier.
getOptions() - Method in class milk.classifiers.MIWrapper: Gets the current settings of the Classifier.
getOptions() - Method in class milk.classifiers.MIRBFNetwork: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.MINND: Gets the current settings of the Classifier.
getOptions() - Method in class milk.classifiers.MILRGEOM: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.MILRARITH: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.MILR: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.MIBoost: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.MDD: Gets the current settings of the classifier.
getOptions() - Method in class milk.classifiers.DD: Gets the current settings of the classifier.
getOptions() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class milk.experiment.MIInstanceQuery: Gets the current settings of InstanceQuery
getOptions() - Method in class milk.experiment.MIExperiment: Gets the current settings of the experiment iterator.
getOptions() - Method in class milk.experiment.MICSVResultListener: Gets the current settings of the Classifier.
getOptions() - Method in class milk.experiment.MICrossValidationResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the current settings of the Classifier.
getOutputFile() - Method in class milk.experiment.MIRandomSplitResultProducer: Get the value of OutputFile.
getOutputFile() - Method in class milk.experiment.MICSVResultListener: Get the value of OutputFile.
getOutputFile() - Method in class milk.experiment.MICrossValidationResultProducer: Get the value of OutputFile.
getPropertyArray() - Method in class milk.experiment.MIExperiment: Gets the array of values to set the custom property to.
getPropertyArrayLength() - Method in class milk.experiment.MIExperiment: Gets the number of custom iterator values that have been defined for the experiment.
getPropertyArrayValue(int) - Method in class milk.experiment.MIExperiment: Gets a specified value from the custom property iterator array.
getPropertyPath() - Method in class milk.experiment.MIExperiment: Gets the path of properties taken to get to the custom property to iterate over.
getQuery() - Method in class milk.experiment.MIInstanceQuery: Get the query to execute against the database
getRandomizeData() - Method in class milk.experiment.MIRandomSplitResultProducer: Get if dataset is to be randomized
getRawOutput() - Method in class milk.experiment.MIRandomSplitResultProducer: Get if raw split evaluator output is to be saved
getRawOutput() - Method in class milk.experiment.MICrossValidationResultProducer: Get if raw split evaluator output is to be saved
getRawResultOutput() - Method in interface milk.experiment.MISplitEvaluator: Returns the raw output for the most recent call to getResult.
getRawResultOutput() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the raw output from the classifier
getRemoteHosts() - Method in class milk.experiment.MIRemoteExperiment: Get the list of remote host names
getResult(Exemplars, Exemplars) - Method in interface milk.experiment.MISplitEvaluator: Gets the results for the supplied train and test datasets.
getResult(Exemplars, Exemplars) - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the results for the supplied train and test datasets.
getResultFromTable(String, MIResultProducer, Object[]) - Method in class milk.experiment.MIDatabaseUtils: Executes a database query to extract a result for the supplied key from the database.
getResultListener() - Method in class milk.experiment.MIExperiment: Gets the result listener where results will be sent.
getResultNames() - Method in interface milk.experiment.MISplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in interface milk.experiment.MIResultProducer: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class milk.experiment.MICrossValidationResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultProducer() - Method in class milk.experiment.MIExperiment: Get the result producer used for the current experiment.
getResultSet() - Method in class milk.experiment.MIDatabaseUtils: Gets the results generated by a previous query.
getResultsTableName(MIResultProducer) - Method in class milk.experiment.MIDatabaseUtils: Gets the name of the experiment table that stores results from a particular ResultProducer.
getResultTypes() - Method in interface milk.experiment.MISplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in interface milk.experiment.MIResultProducer: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class milk.experiment.MICrossValidationResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class milk.experiment.MIClassifierSplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getRidge() - Method in class milk.classifiers.MIRBFNetwork: Get the Ridge value.
getRidge() - Method in class milk.classifiers.MILRGEOM: Gets the ridge in the log-likelihood.
getRidge() - Method in class milk.classifiers.MILRARITH: Gets the ridge in the log-likelihood.
getRidge() - Method in class milk.classifiers.MILR: Gets the ridge in the log-likelihood.
getRunLower() - Method in class milk.experiment.MIExperiment: Get the lower run number for the experiment.
getRunUpper() - Method in class milk.experiment.MIExperiment: Get the upper run number for the experiment.
getSparseData() - Method in class milk.experiment.MIInstanceQuery: Gets whether data is to be returned as a set of sparse instances
getSplitByDataSet() - Method in class milk.experiment.MIRemoteExperiment: Returns true if sub experiments are to be created on the basis of data set..
getSplitEvaluator() - Method in class milk.experiment.MIRandomSplitResultProducer: Get the SplitEvaluator.
getSplitEvaluator() - Method in class milk.experiment.MICrossValidationResultProducer: Get the SplitEvaluator.
getStdDev() - Method in class milk.visualize.DistributionPanel
getTaskStatus() - Method in class milk.experiment.MIRemoteExperimentSubTask
getTimestamp() - Static method in class milk.experiment.MIRandomSplitResultProducer: Gets a Double representing the current date and time.
getTimestamp() - Static method in class milk.experiment.MICrossValidationResultProducer: Gets a Double representing the current date and time.
getTrainPercent() - Method in class milk.experiment.MIRandomSplitResultProducer: Get the value of TrainPercent.
getTransformMethod() - Method in class milk.classifiers.SimpleMI: Get the method used in transformation.
getUpper() - Method in class milk.gui.experiment.MIRunNumberPanel: Gets the current upper run number.
getUsePropertyIterator() - Method in class milk.experiment.MIExperiment: Gets whether the custom property iterator should be used.
getXIndex() - Method in class milk.visualize.GeomPanel
getXIndex() - Method in class milk.visualize.DistributionPanel
getXValue() - Method in class milk.visualize.PlotPanel: Return the current max value of the attribute plotted on the x axis
getYIndex() - Method in class milk.visualize.GeomPanel
globalInfo() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns a string describing this result producer
globalInfo() - Method in class milk.experiment.MIInstancesResultListener: Returns a string describing this result listener
globalInfo() - Method in class milk.experiment.MIDatabaseResultListener: Returns a string describing this result listener
globalInfo() - Method in class milk.experiment.MICSVResultListener: Returns a string describing this result listener
globalInfo() - Method in class milk.experiment.MICrossValidationResultProducer: Returns a string describing this result producer
globalInfo() - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns a string describing this split evaluator

H

hasMoreIterations() - Method in class milk.experiment.MIExperiment: Returns true if there are more iterations to carry out in the experiment.

I

id - Variable in class milk.visualize.MIPanel
idAttribute() - Method in class milk.core.Exemplars: Returns the ID attribute.
idAttribute() - Method in class milk.core.Exemplar: Returns the ID attribute.
idIndex - Variable in class milk.visualize.MIPanel
idIndex() - Method in class milk.core.Exemplars: Returns the ID attribute's index.
idIndex() - Method in class milk.core.Exemplar: Returns the ID attribute's index.
idValue() - Method in class milk.core.Exemplar: Returns the ID attribute's value.
IN_USE - Static variable in class milk.experiment.MIRemoteExperiment
incorrect() - Method in class milk.classifiers.MIEvaluation: Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
incrementFailed(int) - Method in class milk.experiment.MIRemoteExperiment: Increment the overall number of failures and the number of failures for a particular host
incrementFinished() - Method in class milk.experiment.MIRemoteExperiment: Increment the number of successfully completed sub experiments
index - Variable in class milk.visualize.Axis: The attribute index for this axis
initialize() - Method in class milk.experiment.MIRemoteExperiment: Prepares a remote experiment for running, creates sub experiments
initialize() - Method in class milk.experiment.MIExperiment: Prepares an experiment for running, initializing current iterator settings.
insertAttributeAt(Attribute, int) - Method in class milk.core.Exemplars: Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
insertAttributeAt(Attribute, int) - Method in class milk.core.Exemplar: Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
insts - Variable in class milk.visualize.MIPanel
intervalAdded(ListDataEvent) - Method in class milk.visualize.SelectPanel
intervalRemoved(ListDataEvent) - Method in class milk.visualize.SelectPanel
ip - Variable in class milk.visualize.MIPanel
isAllMissing(int) - Method in class milk.core.Exemplar: Check whether the values of the specified attribute in this exemplar are all missing values
isCacheValid(Object[]) - Method in class milk.experiment.MIDatabaseResultListener: Checks whether the current cache contents are valid for the supplied key.
isConnected() - Method in class milk.experiment.MIDatabaseUtils: Returns true if a database connection is active.
isKeyInCache(MIResultProducer, Object[]) - Method in class milk.experiment.MIDatabaseResultListener: Returns true if the supplied key is in the key cache (and thus we do not need to execute a database query).
isKeyInTable(String, MIResultProducer, Object[]) - Method in class milk.experiment.MIDatabaseUtils: Executes a database query to see whether a result for the supplied key is already in the database.
isResultRequired(MIResultProducer, Object[]) - Method in interface milk.experiment.MIResultListener: Determines whether the results for a specified key must be generated.
isResultRequired(MIResultProducer, Object[]) - Method in class milk.experiment.MIDatabaseResultListener: Always says a result is required.
isResultRequired(MIResultProducer, Object[]) - Method in class milk.experiment.MICSVResultListener: Always says a result is required.
isUp - Variable in class milk.visualize.PlotPanel: Whether the distribution curve is up or down

K

kappa() - Method in class milk.classifiers.MIEvaluation: Returns value of kappa statistic if class is nominal.
kullback(double[], double[], double[], double[], int) - Method in class milk.classifiers.MINND: This function calculates the Kullback Leibler distance between two normal distributions.

L

lastExemplar() - Method in class milk.core.Exemplars: Returns the last exemplar in the set.
launchNext(int, int) - Method in class milk.experiment.MIRemoteExperiment: Launch a sub experiment on a remote host
listOptions() - Method in class milk.classifiers.TLDSimple: Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class milk.classifiers.TLD: Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class milk.classifiers.SimpleMI: Returns an enumeration describing the available options.
listOptions() - Method in class milk.classifiers.MIWrapper: Returns an enumeration describing the available options.
listOptions() - Method in class milk.classifiers.MIRBFNetwork: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.MINND: Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class milk.classifiers.MILRGEOM: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.MILRARITH: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.MILR: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.MIBoost: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.MDD: Returns an enumeration describing the available options
listOptions() - Method in class milk.classifiers.DD: Returns an enumeration describing the available options
listOptions() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class milk.experiment.MIInstanceQuery: Returns an enumeration describing the available options
listOptions() - Method in class milk.experiment.MIExperiment: Returns an enumeration describing the available options..
listOptions() - Method in class milk.experiment.MICSVResultListener: Returns an enumeration describing the available options..
listOptions() - Method in class milk.experiment.MICrossValidationResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns an enumeration describing the available options..
loadCache(MIResultProducer, Object[]) - Method in class milk.experiment.MIDatabaseResultListener: Executes a database query to fill the key cache
logMessage(String) - Method in class milk.gui.experiment.MIRunPanel: Sends the supplied message to the log panel log area.

M

m_AddBut - Variable in class milk.gui.experiment.MIDatasetListPanel: Click to add a dataset
m_AdditionalMeasures - Variable in class milk.experiment.MIRandomSplitResultProducer: The names of any additional measures to look for in SplitEvaluators
m_AdditionalMeasures - Variable in class milk.experiment.MIExperiment: Method names of additional measures of objects contained in the custom property iterator.
m_AdditionalMeasures - Variable in class milk.experiment.MICrossValidationResultProducer: The names of any additional measures to look for in SplitEvaluators
m_AdditionalMeasures - Variable in class milk.experiment.MIClassifierSplitEvaluator: The names of any additional measures to look for in SplitEvaluators
m_advanceDataSetFirst - Variable in class milk.gui.experiment.MISetupPanel: Click to advacne data set before custom generator
m_AdvanceDataSetFirst - Variable in class milk.experiment.MIExperiment: If true an experiment will advance the current data set befor any custom itererator
m_advanceIteratorFirst - Variable in class milk.gui.experiment.MISetupPanel: Click to advance custom generator before data set
m_ArffFilter - Variable in class milk.gui.experiment.MIResultsPanel: Filter to ensure only arff files are selected for result files
m_ArffFilter - Variable in class milk.gui.experiment.MIDatasetListPanel: A filter to ensure only arff files get selected
m_ArrayEditor - Variable in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Allows editing of the custom property values
m_Attributes - Variable in class milk.classifiers.MIWrapper: All attribute names
m_Attributes - Variable in class milk.classifiers.MILRGEOM: All attribute names
m_Attributes - Variable in class milk.classifiers.MILRARITH: All attribute names
m_Attributes - Variable in class milk.classifiers.MILR: All attribute names
m_Attributes - Variable in class milk.classifiers.MIBoost: All attribute names
m_Attributes - Variable in class milk.classifiers.MDD: All attribute names
m_Attributes - Variable in class milk.classifiers.DD: All attribute names
m_AttributeTypes - Variable in class milk.experiment.MIInstancesResultListener: Stores the attribute types for each column
m_Beta - Variable in class milk.classifiers.MIBoost: Voting weights of models
m_Cache - Variable in class milk.experiment.MIDatabaseResultListener: Stores the cached values
m_CacheKey - Variable in class milk.experiment.MIDatabaseResultListener: Stores the key for which the cache is valid
m_CacheKeyIndex - Variable in class milk.experiment.MIDatabaseResultListener: Stores the index of the key column holding the cache key data
m_CacheKeyName - Variable in class milk.experiment.MIDatabaseResultListener: Holds the name of the key field to cache upon, or null if no caching
m_Class - Variable in class milk.classifiers.TLDSimple: The class label of each exemplar
m_Class - Variable in class milk.classifiers.TLD: The class label of each exemplar
m_Class - Variable in class milk.classifiers.MINND: The class label of each exemplar
m_Classes - Variable in class milk.classifiers.MILRGEOM: Class labels for each bag
m_Classes - Variable in class milk.classifiers.MILRARITH: Class labels for each bag
m_Classes - Variable in class milk.classifiers.MILR: Class labels for each bag
m_Classes - Variable in class milk.classifiers.MIBoost: Class labels for each bag
m_Classes - Variable in class milk.classifiers.MDD: Class labels for each bag
m_Classes - Variable in class milk.classifiers.DD: Class labels for each bag
m_ClassFirst - Variable in class milk.experiment.MIExperiment: True if the class attribute is the first attribute for all datasets involved in this experiment.
m_ClassFirst - Variable in class milk.gui.experiment.MIExperimenter: True if the class attribute is the first attribute for all datasets involved in this experiment.
m_Classifier - Variable in class milk.classifiers.MIWrapper
m_Classifier - Variable in class milk.classifiers.MIBoost: The model base classifier to use
m_Classifier - Variable in class milk.experiment.MIClassifierSplitEvaluator: The classifier used for evaluation
m_ClassifierOptions - Variable in class milk.experiment.MIClassifierSplitEvaluator: The classifier options (if any)
m_ClassifierVersion - Variable in class milk.experiment.MIClassifierSplitEvaluator: The classifier version
m_ClassIndex - Variable in class milk.classifiers.MIWrapper: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.MILRGEOM: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.MILRARITH: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.MILR: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.MIBoost: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.MDD: The index of the class attribute
m_ClassIndex - Variable in class milk.classifiers.DD: The index of the class attribute
m_clm - Variable in class milk.classifiers.MIRBFNetwork: The RBF filter
m_CompareCombo - Variable in class milk.gui.experiment.MIResultsPanel: Lets the user select which performance measure to analyze
m_CompareModel - Variable in class milk.gui.experiment.MIResultsPanel: The model embedded in m_CompareCombo
m_ConfigureBut - Variable in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Click to select the property to iterate over
m_configureHostNames - Variable in class milk.gui.experiment.MIDistributeExperimentPanel: Popup the HostListPanel
m_ConfigureListener - Variable in class milk.gui.experiment.MIResultsPanel: An actionlisteners that updates ttest settings
m_Connection - Variable in class milk.experiment.MIDatabaseUtils: The database connection
m_CurrentInstances - Variable in class milk.experiment.MIExperiment: The dataset currently being used
m_CurrentProperty - Variable in class milk.experiment.MIExperiment: The custom property value that has actually been set
m_Cutoff - Variable in class milk.classifiers.TLDSimple
m_Cutoff - Variable in class milk.classifiers.TLD
m_Data - Variable in class milk.classifiers.MILRGEOM: MI data
m_Data - Variable in class milk.classifiers.MILRARITH: MI data
m_Data - Variable in class milk.classifiers.MILR: MI data
m_Data - Variable in class milk.classifiers.MDD: MI data
m_Data - Variable in class milk.classifiers.DD: MI data
m_DatabaseURL - Variable in class milk.experiment.MIDatabaseUtils: Database URL
m_DatasetKeyBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to edit the columns used to determine the scheme
m_DatasetKeyLabel - Variable in class milk.gui.experiment.MIResultsPanel: Displays the currently selected column names for the scheme & options
m_DatasetKeyList - Variable in class milk.gui.experiment.MIResultsPanel: Displays the list of selected columns determining the scheme
m_DatasetKeyModel - Variable in class milk.gui.experiment.MIResultsPanel: Stores the list of attributes for selecting the scheme columns
m_DatasetListPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel for configuring selected datasets
m_DatasetModel - Variable in class milk.gui.experiment.MIResultsPanel: The model embedded in m_DatasetCombo
m_DatasetNumber - Variable in class milk.experiment.MIExperiment: The current dataset number when the experiment is running
m_Datasets - Variable in class milk.experiment.MIExperiment: An array of dataset files
m_Debug - Variable in class milk.classifiers.MIWrapper: Debugging output
m_Debug - Variable in class milk.classifiers.MILRGEOM: Debugging output
m_Debug - Variable in class milk.classifiers.MILRARITH: Debugging output
m_Debug - Variable in class milk.classifiers.MILR: Debugging output
m_Debug - Variable in class milk.classifiers.MIBoost: Debugging output
m_Debug - Variable in class milk.classifiers.MDD: Debugging output
m_Debug - Variable in class milk.classifiers.DD: Debugging output
m_Debug - Variable in class milk.experiment.MIDatabaseUtils: True if debugging output should be printed
m_Debug - Variable in class milk.experiment.MIDatabaseResultListener: True if debugging output should be printed
m_debugOutput - Variable in class milk.experiment.MIRandomSplitResultProducer: Save raw output of split evaluators --- for debugging purposes
m_debugOutput - Variable in class milk.experiment.MICrossValidationResultProducer: Save raw output of split evaluators --- for debugging purposes
m_DefaultColors - Variable in class milk.visualize.MIPanel
m_DeleteBut - Variable in class milk.gui.experiment.MIHostListPanel: Click to remove the selected host from the list
m_DeleteBut - Variable in class milk.gui.experiment.MIDatasetListPanel: Click to remove the selected dataset from the list
m_Dimension - Variable in class milk.classifiers.TLDSimple: The dimension of each exemplar, i.e.
m_Dimension - Variable in class milk.classifiers.TLD: The dimension of each exemplar, i.e.
m_Dimension - Variable in class milk.classifiers.MINND: The dimension of each exemplar, i.e.
m_DiscretizeBin - Variable in class milk.classifiers.MIBoost
m_DistributeExperimentPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel for enabling a distributed experiment
m_DistributionPanel - Variable in class milk.visualize.MIExplorer: The panel to show distributions
m_doesProduce - Variable in class milk.experiment.MIClassifierSplitEvaluator: Array of booleans corresponding to the measures in m_AdditionalMeasures indicating which of the AdditionalMeasures the current classifier can produce
m_enableDistributedExperiment - Variable in class milk.gui.experiment.MIDistributeExperimentPanel: Distribute the current experiment to remote hosts
m_Exemplars - Variable in class milk.classifiers.SimpleMI
m_Exp - Variable in class milk.gui.experiment.MISetupPanel: The experiment being configured
m_Exp - Variable in class milk.gui.experiment.MIRunPanel: The experiment to run
m_Exp - Variable in class milk.gui.experiment.MIRunNumberPanel: The experiment being configured
m_Exp - Variable in class milk.gui.experiment.MIResultsPanel: An experiment (used for identifying a result source) -- optional
m_Exp - Variable in class milk.gui.experiment.MIHostListPanel: The remote experiment to set the host list of
m_Exp - Variable in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: The experiment this all applies to
m_Exp - Variable in class milk.gui.experiment.MIDatasetListPanel: The experiment to set the dataset list of
m_ExpFilter - Variable in class milk.gui.experiment.MISetupPanel: A filter to ensure only experiment files get shown in the chooser
m_FileChooser - Variable in class milk.gui.experiment.MISetupPanel: The file chooser for selecting experiments
m_FileChooser - Variable in class milk.gui.experiment.MIResultsPanel: The file chooser for selecting result files
m_FileChooser - Variable in class milk.gui.experiment.MIDatasetListPanel: The file chooser component
m_Filter - Variable in class milk.classifiers.MIBoost
m_Finished - Variable in class milk.experiment.MIExperiment: True if the experiment has finished running
m_FromDBaseBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to load results from a database
m_FromExpBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to get results from the destination given in the experiment
m_FromFileBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to load results from a file
m_FromLab - Variable in class milk.gui.experiment.MIResultsPanel: Displays a message about the current result set
m_GeneratorPropertyPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel that configures iteration on custom resultproducer property
m_GeomPanel - Variable in class milk.visualize.MIExplorer: The panel to show data geometrically
m_History - Variable in class milk.gui.experiment.MIResultsPanel: A panel controlling results viewing
m_HostField - Variable in class milk.gui.experiment.MIHostListPanel: The field with which to enter host names
m_hostList - Variable in class milk.gui.experiment.MIDistributeExperimentPanel: The host list panel
m_IdIndex - Variable in class milk.classifiers.MIWrapper
m_IdIndex - Variable in class milk.classifiers.MILRGEOM
m_IdIndex - Variable in class milk.classifiers.MILRARITH
m_IdIndex - Variable in class milk.classifiers.MILR
m_IdIndex - Variable in class milk.classifiers.MIBoost
m_IdIndex - Variable in class milk.classifiers.MDD
m_IdIndex - Variable in class milk.classifiers.DD
m_InstanceQuery - Variable in class milk.gui.experiment.MIResultsPanel: Does any database querying for us
m_Instances - Variable in class milk.experiment.MIRandomSplitResultProducer: The dataset of interest
m_Instances - Variable in class milk.experiment.MIInstancesResultListener: Stores the instances created so far, before assigning to a header
m_Instances - Variable in class milk.experiment.MICrossValidationResultProducer: The dataset of interest
m_Instances - Variable in class milk.gui.experiment.MIResultsPanel: The instances we're extracting results from
m_List - Variable in class milk.gui.experiment.MIHostListPanel: The component displaying the host list
m_List - Variable in class milk.gui.experiment.MIDatasetListPanel: The component displaying the dataset list
m_Listeners - Variable in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Listeners who want to be notified about editing status of this panel
m_LoadThread - Variable in class milk.gui.experiment.MIResultsPanel: A thread to load results instances from a file or database
m_Log - Variable in class milk.gui.experiment.MIRunPanel
m_logistic - Variable in class milk.classifiers.MIRBFNetwork: The logistic regression model
m_LogPanel - Variable in class milk.visualize.MIExplorer: The panel for log and status messages
m_LowerText - Variable in class milk.gui.experiment.MIRunNumberPanel: Configures the lower run number
m_MaxIterations - Variable in class milk.classifiers.MIBoost
m_Mean - Variable in class milk.classifiers.MINND: The mean for each attribute of each exemplar
m_MeanN - Variable in class milk.classifiers.TLDSimple: The mean for each attribute of each negative exemplar
m_MeanN - Variable in class milk.classifiers.TLD: The mean for each attribute of each negative exemplar
m_MeanP - Variable in class milk.classifiers.TLDSimple: The mean for each attribute of each positive exemplar
m_MeanP - Variable in class milk.classifiers.TLD: The mean for each attribute of each positive exemplar
m_Method - Variable in class milk.classifiers.MIWrapper
m_Models - Variable in class milk.classifiers.MIBoost
m_Neighbour - Variable in class milk.classifiers.MINND: The number of nearest neighbour for prediction
m_NewBut - Variable in class milk.gui.experiment.MISetupPanel: Click to create a new experiment with default settings
m_NominalIndexes - Variable in class milk.experiment.MIInstancesResultListener: For lookup of indices given a string value for each nominal attribute
m_NominalStrings - Variable in class milk.experiment.MIInstancesResultListener: Contains strings seen so far for each nominal attribute
m_Notes - Variable in class milk.experiment.MIExperiment: User notes about the experiment
m_NotesText - Variable in class milk.gui.experiment.MISetupPanel: Area for user notes Default of 5 rows
m_num_clusters - Variable in class milk.classifiers.MIRBFNetwork: The number of clusters to use
m_numberAdditionalMeasures - Variable in class milk.experiment.MIClassifierSplitEvaluator: The number of additional measures that need to be filled in after taking into account column constraints imposed by the final destination for results
m_NumClasses - Variable in class milk.classifiers.TLDSimple: The number of class labels in the data
m_NumClasses - Variable in class milk.classifiers.TLD: The number of class labels in the data
m_NumClasses - Variable in class milk.classifiers.MIWrapper: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.MINND: The number of class labels in the data
m_NumClasses - Variable in class milk.classifiers.MILRGEOM: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.MILRARITH: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.MILR: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.MIBoost: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.MDD: The number of the class labels
m_NumClasses - Variable in class milk.classifiers.DD: The number of the class labels
m_NumFolds - Variable in class milk.experiment.MICrossValidationResultProducer: The number of folds in the cross-validation
m_OpenBut - Variable in class milk.gui.experiment.MISetupPanel: Click to load an experiment
m_Out - Variable in class milk.experiment.MICSVResultListener: The destination for results (typically connected to the output file)
m_OutputFile - Variable in class milk.experiment.MIRandomSplitResultProducer: The destination output file/directory for raw output
m_OutputFile - Variable in class milk.experiment.MICSVResultListener: The destination output file, null sends to System.out
m_OutputFile - Variable in class milk.experiment.MICrossValidationResultProducer: The destination output file/directory for raw output
m_OutText - Variable in class milk.gui.experiment.MIResultsPanel: Displays the output of tests
m_Par - Variable in class milk.classifiers.MILRGEOM
m_Par - Variable in class milk.classifiers.MILRARITH
m_Par - Variable in class milk.classifiers.MILR
m_Par - Variable in class milk.classifiers.MDD
m_Par - Variable in class milk.classifiers.DD
m_ParamsN - Variable in class milk.classifiers.TLDSimple: The parameters to be estimated for each negative exemplar
m_ParamsN - Variable in class milk.classifiers.TLD: The parameters to be estimated for each negative exemplar
m_ParamsP - Variable in class milk.classifiers.TLDSimple: The parameters to be estimated for each positive exemplar
m_ParamsP - Variable in class milk.classifiers.TLD: The parameters to be estimated for each positive exemplar
m_PerformBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to start the test
m_PreprocessPanel - Variable in class milk.visualize.MIExplorer: The panel for preprocessing instances
m_PropertyArray - Variable in class milk.experiment.MIExperiment: The array of values to set the property to
m_PropertyNumber - Variable in class milk.experiment.MIExperiment: The current custom property value index when the experiment is running
m_PropertyPath - Variable in class milk.experiment.MIExperiment: The path to the iterator property
m_randomize - Variable in class milk.experiment.MIRandomSplitResultProducer: Whether dataset is to be randomized
m_Rate - Variable in class milk.classifiers.MINND: The learning rate in the gradient descent
m_relativeCheck - Variable in class milk.gui.experiment.MIDatasetListPanel: Make file paths relative to the user (start) directory
m_remoteHosts - Variable in class milk.experiment.MIRemoteExperiment: Holds the names of machines with remoteEngine servers running
m_result - Variable in class milk.experiment.MIClassifierSplitEvaluator: Holds the statistics for the most recent application of the classifier
m_ResultKeyBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to edit the columns used to determine the scheme
m_ResultKeyLabel - Variable in class milk.gui.experiment.MIResultsPanel: Displays the currently selected column names for the scheme & options
m_ResultKeyList - Variable in class milk.gui.experiment.MIResultsPanel: Displays the list of selected columns determining the scheme
m_ResultKeyModel - Variable in class milk.gui.experiment.MIResultsPanel: Stores the list of attributes for selecting the scheme columns
m_ResultListener - Variable in class milk.experiment.MIRandomSplitResultProducer: The ResultListener to send results to
m_ResultListener - Variable in class milk.experiment.MIExperiment: Where results will be sent
m_ResultListener - Variable in class milk.experiment.MICrossValidationResultProducer: The ResultListener to send results to
m_ResultProducer - Variable in class milk.experiment.MIExperiment: The result producer
m_ResultProducer - Variable in class milk.experiment.MIDatabaseResultListener: The ResultProducer to listen to
m_ResultsPanel - Variable in class milk.gui.experiment.MIExperimenter: The panel for analysing experimental results
m_ResultsTableName - Variable in class milk.experiment.MIDatabaseResultListener: The name of the current results table
m_ridge - Variable in class milk.classifiers.MIRBFNetwork: The ridge regression coefficient for logistic regression
m_Ridge - Variable in class milk.classifiers.MILRGEOM: The ridge parameter.
m_Ridge - Variable in class milk.classifiers.MILRARITH: The ridge parameter.
m_Ridge - Variable in class milk.classifiers.MILR: The ridge parameter.
m_RLEditor - Variable in class milk.gui.experiment.MISetupPanel: The ResultListener editor
m_RLEditorPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel to contain the ResultListener editor
m_RP - Variable in class milk.experiment.MICSVResultListener: The MIResultProducer sending us results
m_RPEditor - Variable in class milk.gui.experiment.MISetupPanel: The ResultProducer editor
m_RPEditorPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel to contain the ResultProducer editor
m_Run - Variable in class milk.classifiers.TLDSimple
m_Run - Variable in class milk.classifiers.TLD
m_RunCombo - Variable in class milk.gui.experiment.MIResultsPanel: Lets the user select which column contains the run number
m_RunLower - Variable in class milk.experiment.MIExperiment: Lower run number
m_RunModel - Variable in class milk.gui.experiment.MIResultsPanel: The model embedded in m_RunCombo
m_RunNumber - Variable in class milk.experiment.MIExperiment: The current run number when the experiment is running
m_RunNumberPanel - Variable in class milk.gui.experiment.MISetupPanel: The panel for configuring run numbers
m_RunPanel - Variable in class milk.gui.experiment.MIExperimenter: The panel for running the experiment
m_RunThread - Variable in class milk.gui.experiment.MIRunPanel: The thread running the experiment
m_RunUpper - Variable in class milk.experiment.MIExperiment: Upper run number
m_SaveBut - Variable in class milk.gui.experiment.MISetupPanel: Click to save an experiment
m_SaveOutBut - Variable in class milk.gui.experiment.MIResultsPanel: Click to save test output to a file
m_Seed - Variable in class milk.classifiers.TLDSimple
m_Seed - Variable in class milk.classifiers.TLD
m_SetupPanel - Variable in class milk.gui.experiment.MIExperimenter: The panel for configuring the experiment
m_SgmSqN - Variable in class milk.classifiers.TLDSimple: Estimated sigma^2 in negative bags
m_SgmSqP - Variable in class milk.classifiers.TLDSimple: Estimated sigma^2 in positive bags
m_ShowStdDevs - Variable in class milk.gui.experiment.MIResultsPanel: Lets the user select whether standard deviations are to be output or not
m_SigTex - Variable in class milk.gui.experiment.MIResultsPanel: Lets the user edit the test significance
m_splitByDataSet - Variable in class milk.experiment.MIRemoteExperiment: If true, then sub experiments are created on the basis of data sets rather than run number.
m_splitByDataSet - Variable in class milk.gui.experiment.MIDistributeExperimentPanel: Split experiment up by data set.
m_splitByRun - Variable in class milk.gui.experiment.MIDistributeExperimentPanel: Split experiment up by run number.
m_SplitEvaluator - Variable in class milk.experiment.MIRandomSplitResultProducer: The SplitEvaluator used to generate results
m_SplitEvaluator - Variable in class milk.experiment.MICrossValidationResultProducer: The SplitEvaluator used to generate results
m_StartBut - Variable in class milk.gui.experiment.MIRunPanel: Click to start running the experiment
m_Statement - Variable in class milk.experiment.MIDatabaseUtils: The statement used for database queries
m_StatusBox - Variable in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Controls whether the custom iterator is used or not
m_StopBut - Variable in class milk.gui.experiment.MIRunPanel: Click to signal the running experiment to halt
m_subExpComplete - Variable in class milk.experiment.MIRemoteExperiment: The status of each of the sub-experiments
m_subExperiments - Variable in class milk.experiment.MIRemoteExperiment: The sub experiments
m_SumN - Variable in class milk.classifiers.TLDSimple: The effective sum of weights of each negative exemplar in each dimension
m_SumN - Variable in class milk.classifiers.TLD: The effective sum of weights of each negative exemplar in each dimension
m_SumP - Variable in class milk.classifiers.TLDSimple: The effective sum of weights of each positive exemplar in each dimension
m_SumP - Variable in class milk.classifiers.TLD: The effective sum of weights of each positive exemplar in each dimension
m_Support - Variable in class milk.gui.experiment.MISetupPanel: Manages sending notifications to people when we change the experiment, at this stage, only the resultlistener so the resultpanel can update.
m_TabbedPane - Variable in class milk.gui.experiment.MIExperimenter: The tabbed pane that controls which sub-pane we are working with
m_TabbedPane - Variable in class milk.visualize.MIExplorer: The tabbed pane that controls which sub-pane we are working with
m_TestsButton - Variable in class milk.gui.experiment.MIResultsPanel: Lets the user select which scheme to base comparisons against
m_TestsList - Variable in class milk.gui.experiment.MIResultsPanel: Holds the list of schemes to base the test against
m_TestsModel - Variable in class milk.gui.experiment.MIResultsPanel: The model embedded in m_TestsList
m_TrainPercent - Variable in class milk.experiment.MIRandomSplitResultProducer: The percentage of instances to use for training
m_TransformMethod - Variable in class milk.classifiers.SimpleMI
m_TTester - Variable in class milk.gui.experiment.MIResultsPanel: The PairedTTester object
m_UpperText - Variable in class milk.gui.experiment.MIRunNumberPanel: Configures the upper run number
m_UseEmpiricalCutOff - Variable in class milk.classifiers.TLDSimple
m_UseEmpiricalCutOff - Variable in class milk.classifiers.TLD
m_UsePropertyIterator - Variable in class milk.experiment.MIExperiment: True if the exp should also iterate over a property of the RP
m_UserDir - Variable in class milk.gui.experiment.MIDatasetListPanel: The user (start) directory
m_Variance - Variable in class milk.classifiers.MINND: The variance for each attribute of each exemplar
m_VarianceN - Variable in class milk.classifiers.TLD: The variance for each attribute of each negative exemplar
m_VarianceP - Variable in class milk.classifiers.TLD: The variance for each attribute of each positive exemplar
m_Weights - Variable in class milk.classifiers.MINND: The weight of each exemplar
m_ZipDest - Variable in class milk.experiment.MIRandomSplitResultProducer: The output zipper to use for saving raw splitEvaluator output
m_ZipDest - Variable in class milk.experiment.MICrossValidationResultProducer: The output zipper to use for saving raw splitEvaluator output
main(String[]) - Static method in class milk.classifiers.TLDSimple: Main method for testing.
main(String[]) - Static method in class milk.classifiers.TLD: Main method for testing.
main(String[]) - Static method in class milk.classifiers.SimpleMI: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MIWrapper: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MIRBFNetwork: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MINND: Main method for testing.
main(String[]) - Static method in class milk.classifiers.MILRGEOM: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MILRARITH: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MILR: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MIEvaluation: A test method for this class.
main(String[]) - Static method in class milk.classifiers.MIBoost: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.MDD: Main method for testing this class.
main(String[]) - Static method in class milk.classifiers.DD: Main method for testing this class.
main(String[]) - Static method in class milk.core.Exemplars: Main method for this class -- just performone run of 10-fold CV and prints out the set.
main(String[]) - Static method in class milk.core.Exemplar: Main method for testing this class -- just prints out a set of Exemplars.
main(String[]) - Static method in class milk.data.TLDSimpleData
main(String[]) - Static method in class milk.data.TLDData
main(String[]) - Static method in class milk.data.MIDataSample
main(String[]) - Static method in class milk.data.MIDataPopulation
main(String[]) - Static method in class milk.data.BagStats
main(String[]) - Static method in class milk.experiment.MIRemoteExperiment: Configures/Runs the Experiment from the command line.
main(String[]) - Static method in class milk.experiment.MIInstanceQuery: Test the class from the command line.
main(String[]) - Static method in class milk.experiment.MIExperiment: Configures/Runs the MIExperiment from the command line.
main(String[]) - Static method in class milk.experiment.MICrossValidationResultProducer
main(String[]) - Static method in class milk.gui.experiment.MISetupPanel: Tests out the experiment setup from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIRunPanel: Tests out the run panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIRunNumberPanel: Tests out the panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIResultsPanel: Tests out the results panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIHostListPanel: Tests out the host list panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Tests out the panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIExperimenter: Tests out the experiment environment.
main(String[]) - Static method in class milk.gui.experiment.MIDistributeExperimentPanel: Tests out the panel from the command line.
main(String[]) - Static method in class milk.gui.experiment.MIDatasetListPanel: Tests out the dataset list panel from the command line.
main(String[]) - Static method in class milk.visualize.SelectPanel: Main function for testing, it simply display the two list controls
main(String[]) - Static method in class milk.visualize.MIExplorer: Tests out the explorer environment.
makeCopies(MIClassifier, int) - Static method in class milk.classifiers.MIClassifier: Creates copies of the current classifier, which can then be used for boosting etc.
MAX_FAILURES - Static variable in class milk.experiment.MIRemoteExperiment: allow at most 3 failures on a host before it is removed from the list of usable hosts
MAX_PRECISION - Static variable in class milk.visualize.PlotPanel: precision constant
maxC - Variable in class milk.visualize.MIPanel
maxValue - Variable in class milk.visualize.Axis: The max and min values in the axis
maxY - Variable in class milk.visualize.PlotPanel: The maximal value in Y axis
MDD - class milk.classifiers.MDD.: Modified DD, with collective assumption
MDD() - Constructor for class milk.classifiers.MDD
meanAbsoluteError() - Method in class milk.classifiers.MIEvaluation: Returns the mean absolute error.
meanOrMode() - Method in class milk.core.Exemplar: Returns the mean (mode) for all attributes (except ID and class) as a floating-point value.
meanPriorAbsoluteError() - Method in class milk.classifiers.MIEvaluation: Returns the mean absolute error of the prior.
MIBoost - class milk.classifiers.MIBoost.: MI AdaBoost method, consider the geometric mean of posterior of instances inside a bag (arithmatic mean of log-posterior) and the expectation for a bag is taken inside the loss function.
MIBoost() - Constructor for class milk.classifiers.MIBoost
MIClassifier - class milk.classifiers.MIClassifier.: Abstract classifier.
MIClassifier() - Constructor for class milk.classifiers.MIClassifier
MIClassifierSplitEvaluator - class milk.experiment.MIClassifierSplitEvaluator.: A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
MIClassifierSplitEvaluator() - Constructor for class milk.experiment.MIClassifierSplitEvaluator: No args constructor.
MICrossValidationResultProducer - class milk.experiment.MICrossValidationResultProducer.: Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
MICrossValidationResultProducer() - Constructor for class milk.experiment.MICrossValidationResultProducer
MICSVResultListener - class milk.experiment.MICSVResultListener.: MICSVResultListener outputs the received results in csv format to a Writer
MICSVResultListener() - Constructor for class milk.experiment.MICSVResultListener
MIDatabaseResultListener - class milk.experiment.MIDatabaseResultListener.: DatabaseResultListener takes the results from a ResultProducer and submits them to a central database.
MIDatabaseResultListener() - Constructor for class milk.experiment.MIDatabaseResultListener: Sets up the database drivers
MIDatabaseUtils - class milk.experiment.MIDatabaseUtils.: DatabaseUtils provides utility functions for accessing the experiment database.
MIDatabaseUtils() - Constructor for class milk.experiment.MIDatabaseUtils: Sets up the database drivers
MIDataPopulation - class milk.data.MIDataPopulation.: Generate n-dimensional 2-class MI data using instance-based approach population version
MIDataPopulation() - Constructor for class milk.data.MIDataPopulation
MIDataSample - class milk.data.MIDataSample.: Generate n-dimensional 2-class MI data using instance-based approach sample version
MIDataSample() - Constructor for class milk.data.MIDataSample
MIDatasetListPanel - class milk.gui.experiment.MIDatasetListPanel.: This panel controls setting a list of datasets for an experiment to iterate over.
MIDatasetListPanel() - Constructor for class milk.gui.experiment.MIDatasetListPanel: Create the dataset list panel initially disabled.
MIDatasetListPanel(MIExperiment) - Constructor for class milk.gui.experiment.MIDatasetListPanel: Creates the dataset list panel with the given experiment.
MIDistributeExperimentPanel - class milk.gui.experiment.MIDistributeExperimentPanel.: This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
MIDistributeExperimentPanel() - Constructor for class milk.gui.experiment.MIDistributeExperimentPanel: Constructor
MIDistributeExperimentPanel(MIExperiment) - Constructor for class milk.gui.experiment.MIDistributeExperimentPanel: Creates the panel with the supplied initial experiment.
MIEvaluation - class milk.classifiers.MIEvaluation.: Class for evaluating machine learning models.
MIEvaluation(Exemplars) - Constructor for class milk.classifiers.MIEvaluation: Initializes all the counters for the evaluation.
MIEvaluation(Exemplars, CostMatrix) - Constructor for class milk.classifiers.MIEvaluation: Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
MIExperiment - class milk.experiment.MIExperiment.: Holds all the necessary configuration information for a standard type experiment.
MIExperiment() - Constructor for class milk.experiment.MIExperiment
MIExperimenter - class milk.gui.experiment.MIExperimenter.: The main class for the experiment environment.
MIExperimenter(boolean) - Constructor for class milk.gui.experiment.MIExperimenter: Creates the experiment environment gui with no initial experiment
MIExplorer - class milk.visualize.MIExplorer.: This class puts all components together to visualize the MI data, i.e.
MIExplorer() - Constructor for class milk.visualize.MIExplorer: Creates the environment
MIGeneratorPropertyIteratorPanel - class milk.gui.experiment.MIGeneratorPropertyIteratorPanel.: This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.
MIGeneratorPropertyIteratorPanel() - Constructor for class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Creates the property iterator panel initially disabled.
MIGeneratorPropertyIteratorPanel(MIExperiment) - Constructor for class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Creates the property iterator panel and sets the experiment.
MIHostListPanel - class milk.gui.experiment.MIHostListPanel.: This panel controls setting a list of hosts for a RemoteExperiment to use.
MIHostListPanel() - Constructor for class milk.gui.experiment.MIHostListPanel: Create the host list panel initially disabled.
MIHostListPanel(MIRemoteExperiment) - Constructor for class milk.gui.experiment.MIHostListPanel: Creates the host list panel with the given experiment.
MIInstanceQuery - class milk.experiment.MIInstanceQuery.: Convert the results of a database query into instances.
MIInstanceQuery() - Constructor for class milk.experiment.MIInstanceQuery: Sets up the database drivers
MIInstancesResultListener - class milk.experiment.MIInstancesResultListener.: InstancesResultListener outputs the received results in arff format to a Writer.
MIInstancesResultListener() - Constructor for class milk.experiment.MIInstancesResultListener
milk.classifiers - package milk.classifiers
milk.core - package milk.core
milk.data - package milk.data
milk.experiment - package milk.experiment
milk.gui.experiment - package milk.gui.experiment
milk.visualize - package milk.visualize
MILR - class milk.classifiers.MILR.: Use MI assumption but within LR Valid options are:
MILR() - Constructor for class milk.classifiers.MILR
MILRARITH - class milk.classifiers.MILRARITH.: Using collective assumption, arithmatic average of the posteriors of instances inside a bag is taken.
MILRARITH() - Constructor for class milk.classifiers.MILRARITH
MILRGEOM - class milk.classifiers.MILRGEOM.: Normalized goemetric mean is taken on the posteriors of instances, regardless of class labels Valid options are:
MILRGEOM() - Constructor for class milk.classifiers.MILRGEOM
minC - Variable in class milk.visualize.MIPanel
minimax(Instances, int) - Static method in class milk.classifiers.SimpleMI: Get the minimal and maximal value of a certain attribute in a certain data
MINND - class milk.classifiers.MINND.: 0657.591B Dissertation Multiple-Instance Nearest Neighbour with Distribution learner .
MINND() - Constructor for class milk.classifiers.MINND
minValue - Variable in class milk.visualize.Axis: The max and min values in the axis
MIPanel - class milk.visualize.MIPanel.: This class implements a panel that allows user to select some exemplars to show the visualization.
MIPanel() - Constructor for class milk.visualize.MIPanel: Constructor: it has 2 comboboxes to select Id and class of exemplars respectively, and one ClassPanel to show the class labels
MIPlot2D - class milk.visualize.MIPlot2D.: This class is similar to the Plot2D class except that it also draws the ID of exemplar on each instance point.
MIPlot2D() - Constructor for class milk.visualize.MIPlot2D: Constructor
MIRandomSplitResultProducer - class milk.experiment.MIRandomSplitResultProducer.: Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.
MIRandomSplitResultProducer() - Constructor for class milk.experiment.MIRandomSplitResultProducer
MIRBFNetwork - class milk.classifiers.MIRBFNetwork.: Multi-instance RBF network.
MIRBFNetwork() - Constructor for class milk.classifiers.MIRBFNetwork
MIRemoteExperiment - class milk.experiment.MIRemoteExperiment.: Holds all the necessary configuration information for a distributed experiment.
MIRemoteExperiment(MIExperiment) - Constructor for class milk.experiment.MIRemoteExperiment: Construct a new MIRemoteExperiment using a base Experiment
MIRemoteExperimentSubTask - class milk.experiment.MIRemoteExperimentSubTask.: Class to encapsulate an experiment as a task that can be executed on a remote host.
MIRemoteExperimentSubTask() - Constructor for class milk.experiment.MIRemoteExperimentSubTask
MIResultListener - interface milk.experiment.MIResultListener.: Interface for objects able to listen for results obtained by a ResultProducer
MIResultProducer - interface milk.experiment.MIResultProducer.: This interface defines the methods required for an object that produces results for different randomizations of a dataset.
MIResultsPanel - class milk.gui.experiment.MIResultsPanel.: This panel controls simple analysis of experimental results.
MIResultsPanel() - Constructor for class milk.gui.experiment.MIResultsPanel: Creates the results panel with no initial experiment.
MIRunNumberPanel - class milk.gui.experiment.MIRunNumberPanel.: This panel controls configuration of lower and upper run numbers in an experiment.
MIRunNumberPanel() - Constructor for class milk.gui.experiment.MIRunNumberPanel: Creates the panel with no initial experiment.
MIRunNumberPanel(MIExperiment) - Constructor for class milk.gui.experiment.MIRunNumberPanel: Creates the panel with the supplied initial experiment.
MIRunPanel - class milk.gui.experiment.MIRunPanel.: This panel controls the running of an experiment.
MIRunPanel() - Constructor for class milk.gui.experiment.MIRunPanel: Creates the run panel with no initial experiment.
MIRunPanel(MIExperiment) - Constructor for class milk.gui.experiment.MIRunPanel: Creates the panel with the supplied initial experiment.
MISetupPanel - class milk.gui.experiment.MISetupPanel.: This panel controls the configuration of an experiment.
MISetupPanel() - Constructor for class milk.gui.experiment.MISetupPanel: Creates the setup panel with no initial experiment.
MISetupPanel(MIExperiment) - Constructor for class milk.gui.experiment.MISetupPanel: Creates the setup panel with the supplied initial experiment.
MISplitEvaluator - interface milk.experiment.MISplitEvaluator.: Interface to objects able to generate a fixed set of results for a particular split of a dataset.
MITransform - interface milk.classifiers.MITransform.: Interface to transform any MI data into data suitable for mono-instance learner
MIUpdateableClassifier - interface milk.classifiers.MIUpdateableClassifier.: Interface to incremental classification models that can learn using one exemplar at a time.
MIWrapper - class milk.classifiers.MIWrapper.: Weighted Wrapper method from Eibe Valid options are:
MIWrapper() - Constructor for class milk.classifiers.MIWrapper

N

nextIteration() - Method in class milk.experiment.MIRemoteExperiment: Overides the one in Experiment
nextIteration() - Method in class milk.experiment.MIExperiment: Carries out the next iteration of the experiment.
nextPoint(double) - Method in class milk.data.MIDataPopulation
nextPoint(double, Random, double) - Method in class milk.data.MIDataSample
NO_SOURCE - Static variable in class milk.gui.experiment.MIResultsPanel: Message shown when no experimental results have been loaded
NOT_RUNNING - Static variable in class milk.gui.experiment.MIRunPanel: The message displayed when no experiment is running
numAttributes() - Method in class milk.core.Exemplars: Returns the number of attributes.
numClasses() - Method in class milk.core.Exemplars: Returns the number of class labels.
numExemplars() - Method in class milk.classifiers.MIEvaluation: Gets the number of test exemplars that had a known class value (actually the sum of the weights of test exemplars with known class value).
numExemplars() - Method in class milk.core.Exemplars: Returns the number of exemplars in the set.
numFalseNegatives(int) - Method in class milk.classifiers.MIEvaluation: Calculate number of false negatives with respect to a particular class.
numFalsePositives(int) - Method in class milk.classifiers.MIEvaluation: Calculate number of false positives with respect to a particular class.
numFoldsTipText() - Method in class milk.experiment.MICrossValidationResultProducer: Returns the tip text for this property
numIds() - Method in class milk.core.Exemplar: Returns the number of ID labels.
numsInstances() - Method in class milk.core.Exemplars: Returns the number of instances in the dataset.
numTrueNegatives(int) - Method in class milk.classifiers.MIEvaluation: Calculate the number of true negatives with respect to a particular class.
numTruePositives(int) - Method in class milk.classifiers.MIEvaluation: Calculate the number of true positives with respect to a particular class.

O

outputFileTipText() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the tip text for this property
outputFileTipText() - Method in class milk.experiment.MICSVResultListener: Returns the tip text for this property
outputFileTipText() - Method in class milk.experiment.MICrossValidationResultProducer: Returns the tip text for this property

P

paintComponent(Graphics) - Method in class milk.visualize.SelectPanel
paintComponent(Graphics) - Method in class milk.visualize.PlotPanel: Renders this component
paintComponent(Graphics) - Method in class milk.visualize.MIPlot2D: Renders this component
paintComponent(Graphics) - Method in class milk.visualize.MIPanel: Render this component.
pctCorrect() - Method in class milk.classifiers.MIEvaluation: Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
pctIncorrect() - Method in class milk.classifiers.MIEvaluation: Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
pctUnclassified() - Method in class milk.classifiers.MIEvaluation: Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
performTest() - Method in class milk.gui.experiment.MIResultsPanel: Carries out a t-test using the current configuration.
plotExemplars - Variable in class milk.visualize.PlotPanel: The exemplars to be plotted
plotExemplars - Variable in class milk.visualize.MIPlot2D: The instances to be plotted
PlotPanel - class milk.visualize.PlotPanel.: This class implements a panel that display the distributions of the selected exemplars.
PlotPanel() - Constructor for class milk.visualize.PlotPanel: Constructor
postProcess() - Method in interface milk.experiment.MIResultProducer: Perform any postprocessing.
postProcess() - Method in class milk.experiment.MIRemoteExperiment: overides the one in Experiment
postProcess() - Method in class milk.experiment.MIRandomSplitResultProducer: Perform any postprocessing.
postProcess() - Method in class milk.experiment.MIExperiment: Signals that the experiment is finished running, so that cleanup can be done.
postProcess() - Method in class milk.experiment.MICrossValidationResultProducer: Perform any postprocessing.
postProcess(MIResultProducer) - Method in interface milk.experiment.MIResultListener: Perform any postprocessing.
postProcess(MIResultProducer) - Method in class milk.experiment.MIInstancesResultListener: Perform any postprocessing.
postProcess(MIResultProducer) - Method in class milk.experiment.MIDatabaseResultListener: Perform any postprocessing.
postProcess(MIResultProducer) - Method in class milk.experiment.MICSVResultListener: Perform any postprocessing.
precision(int) - Method in class milk.classifiers.MIEvaluation: Calculate the precision with respect to a particular class.
preProcess() - Method in interface milk.experiment.MIResultProducer: Prepare to generate results.
preProcess() - Method in class milk.experiment.MIRandomSplitResultProducer: Prepare to generate results.
preProcess() - Method in class milk.experiment.MICrossValidationResultProducer: Prepare to generate results.
preprocess(Exemplars, int) - Method in class milk.classifiers.MINND: Pre-process the given exemplar according to the other exemplars in the given exemplars.
preProcess(MIResultProducer) - Method in interface milk.experiment.MIResultListener: Prepare for the results to be received.
preProcess(MIResultProducer) - Method in class milk.experiment.MIInstancesResultListener: Prepare for the results to be received.
preProcess(MIResultProducer) - Method in class milk.experiment.MIDatabaseResultListener: Prepare for the results to be received.
preProcess(MIResultProducer) - Method in class milk.experiment.MICSVResultListener: Prepare for the results to be received.
PROPERTIES - Static variable in class milk.experiment.MIDatabaseUtils: Properties associated with the database connection
PROPERTY_FILE - Static variable in class milk.experiment.MIDatabaseUtils: The name of the properties file
propertyChange(PropertyChangeEvent) - Method in class milk.visualize.SelectPanel: The handler function when property changes are informed.
propertyChange(PropertyChangeEvent) - Method in class milk.visualize.PlotPanel: The handler function when property changes are informed.
propertyChange(PropertyChangeEvent) - Method in class milk.visualize.MIPlot2D: The handler function when property changes are informed.
putResultInTable(String, MIResultProducer, Object[], Object[]) - Method in class milk.experiment.MIDatabaseUtils: Executes a database query to insert a result for the supplied key into the database.

Q

queryTipText() - Method in class milk.experiment.MIInstanceQuery: Returns the tip text for this property

R

randomize(Random) - Method in class milk.core.Exemplars: Shuffles the exemplars in the set so that they are ordered randomly.
randomizeDataTipText() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the tip text for this property
rawOutputTipText() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the tip text for this property
rawOutputTipText() - Method in class milk.experiment.MICrossValidationResultProducer: Returns the tip text for this property
recall(int) - Method in class milk.classifiers.MIEvaluation: Calculate the recall with respect to a particular class.
relationName() - Method in class milk.core.Exemplars: Returns the relation's name.
relativeAbsoluteError() - Method in class milk.classifiers.MIEvaluation: Returns the relative absolute error.
removePropertyChangeListener(PropertyChangeListener) - Method in class milk.gui.experiment.MISetupPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.SelectPanel: Remove the property change listener to hear the change of "addedExs" property of this class.
removePropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.MIPanel: Remove the property change listener to hear the change of color and "exemplars" property of this class.
removePropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.GeomPanel: Remove the property change listener to hear the change of "XAxis" and "YAxis" property of this class.
removePropertyChangeListener(PropertyChangeListener) - Method in class milk.visualize.DistributionPanel: Remove the property change listener to hear the change of "XAxis" and "SD" property of this class.
renameAttribute(Attribute, String) - Method in class milk.core.Exemplars: Renames an attribute.
renameAttribute(int, String) - Method in class milk.core.Exemplars: Renames an attribute.
renameAttributeValue(Attribute, String, String) - Method in class milk.core.Exemplars: Renames the value of a nominal (or string) attribute value.
renameAttributeValue(int, int, String) - Method in class milk.core.Exemplars: Renames the value of a nominal (or string) attribute value.
resample(Random) - Method in class milk.core.Exemplars: Creates a new Exemplars of the same size using random sampling with replacement.
resampleWithWeights(Random) - Method in class milk.core.Exemplars: Creates a new Exemplars of the same size using random sampling with replacement according to the current exemplar weights.
resampleWithWeights(Random, double[]) - Method in class milk.core.Exemplars: Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
retrieveInstances() - Method in class milk.experiment.MIInstanceQuery: Makes a database query using the query set through the -Q option to convert a table into a set of instances
retrieveInstances(String) - Method in class milk.experiment.MIInstanceQuery: Makes a database query to convert a table into a set of instances
rootMeanPriorSquaredError() - Method in class milk.classifiers.MIEvaluation: Returns the root mean prior squared error.
rootMeanSquaredError() - Method in class milk.classifiers.MIEvaluation: Returns the root mean squared error.
rootRelativeSquaredError() - Method in class milk.classifiers.MIEvaluation: Returns the root relative squared error if the class is numeric.
RUN_FIELD_NAME - Static variable in class milk.experiment.MIRandomSplitResultProducer
RUN_FIELD_NAME - Static variable in class milk.experiment.MICrossValidationResultProducer
runExperiment() - Method in class milk.experiment.MIRemoteExperiment: Overides runExperiment in Experiment
runExperiment() - Method in class milk.experiment.MIExperiment: Runs all iterations of the experiment, continuing past errors.

S

saveBuffer() - Method in class milk.gui.experiment.MIResultsPanel: Save the currently selected result buffer to a file.
SelectPanel - class milk.visualize.SelectPanel.: This class implements two list controls which can be used to select exemplars to be shown on the panel.
SelectPanel() - Constructor for class milk.visualize.SelectPanel: Constructor: arrange the display
selectProperty() - Method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Gets the user to select a property of the current resultproducer.
setAdditionalMeasures(String[]) - Method in interface milk.experiment.MISplitEvaluator: Sets a list of method names for additional measures to look for in MISplitEvaluators.
setAdditionalMeasures(String[]) - Method in interface milk.experiment.MIResultProducer: Sets a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class milk.experiment.MIRandomSplitResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class milk.experiment.MICrossValidationResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class milk.experiment.MIClassifierSplitEvaluator: Set a list of method names for additional measures to look for in Classifiers.
setAdvanceDataSetFirst(boolean) - Method in class milk.experiment.MIExperiment: Set the value of m_AdvanceDataSetFirst.
setBaseExperiment(MIExperiment) - Method in class milk.experiment.MIRemoteExperiment: Set the base experiment.
setCacheKeyName(String) - Method in class milk.experiment.MIDatabaseResultListener: Set the value of CacheKeyName.
setClassForIRStatistics(int) - Method in class milk.experiment.MIClassifierSplitEvaluator: Set the value of ClassForIRStatistics.
setClassifier(Classifier) - Method in class milk.classifiers.MIWrapper: Set the base classifier.
setClassifier(Classifier) - Method in class milk.classifiers.MIBoost: Set the classifier for boosting.
setClassifier(MIClassifier) - Method in class milk.experiment.MIClassifierSplitEvaluator: Sets the classifier.
setClassifierName(String) - Method in class milk.experiment.MIClassifierSplitEvaluator: Set the Classifier to use, given it's class name.
setClassIndex(int) - Method in class milk.visualize.MIPanel
setClassValue(double) - Method in class milk.core.Exemplar: Sets the class value of the exemplar
setColors(FastVector) - Method in class milk.visualize.SelectPanel
setColours(FastVector) - Method in class milk.visualize.PlotPanel: Set a list of colours to use when colouring points according to class values or cluster numbers
setComboSizes() - Method in class milk.gui.experiment.MIResultsPanel: Sets the combo-boxes to a fixed size so they don't take up too much room that would be better devoted to the test output box
setDatabaseURL(String) - Method in class milk.experiment.MIDatabaseUtils: Set the value of DatabaseURL.
setDatasetKeyFromDialog() - Method in class milk.gui.experiment.MIResultsPanel
setDatasets(DefaultListModel) - Method in class milk.experiment.MIRemoteExperiment: Set the datasets to use in the experiment
setDatasets(DefaultListModel) - Method in class milk.experiment.MIExperiment: Set the datasets to use in the experiment
setDebug(boolean) - Method in class milk.classifiers.MIWrapper: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.MILRGEOM: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.MILRARITH: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.MILR: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.MIBoost: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.MDD: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class milk.classifiers.DD: Sets whether debugging output will be printed.
setDiscretizeBin(int) - Method in class milk.classifiers.MIBoost: Set the number of bins in discretization
setExemplars(Exemplars) - Method in class milk.visualize.SelectPanel
setExperiment(MIExperiment) - Method in class milk.experiment.MIRemoteExperimentSubTask: Set the experiment for this sub task
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MISetupPanel: Sets the experiment to configure.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIRunPanel: Sets the experiment the panel operates on.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIRunNumberPanel: Sets the experiment to be configured.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIResultsPanel: Tells the panel to use a new experiment.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIGeneratorPropertyIteratorPanel: Sets the experiment which will have the custom properties edited.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIDistributeExperimentPanel: Sets the experiment to be configured.
setExperiment(MIExperiment) - Method in class milk.gui.experiment.MIDatasetListPanel: Tells the panel to act on a new experiment.
setExperiment(MIRemoteExperiment) - Method in class milk.gui.experiment.MIHostListPanel: Tells the panel to act on a new experiment.
setFromExpEnabled() - Method in class milk.gui.experiment.MIResultsPanel: Updates whether the current experiment is of a type that we can determine the results destination.
setIdIndex(int) - Method in class milk.visualize.MIPanel
setInstances(Exemplars) - Method in interface milk.experiment.MIResultProducer: Sets the dataset that results will be obtained for.
setInstances(Exemplars) - Method in class milk.experiment.MIRandomSplitResultProducer: Sets the dataset that results will be obtained for.
setInstances(Exemplars) - Method in class milk.experiment.MICrossValidationResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class milk.gui.experiment.MIResultsPanel: Sets up the panel with a new set of instances, attempting to guess the correct settings for various columns.
setInstances(Instances) - Method in class milk.visualize.MIPanel
setInstances(Instances) - Method in class milk.visualize.GeomPanel
setInstances(Instances) - Method in class milk.visualize.DistributionPanel
setInstancesFromDatabaseTable(String) - Method in class milk.gui.experiment.MIResultsPanel: Queries a database to load results from the specified table name.
setInstancesFromDBaseQuery() - Method in class milk.gui.experiment.MIResultsPanel: Queries the user enough to make a database query to retrieve experiment results.
setInstancesFromExp(MIExperiment) - Method in class milk.gui.experiment.MIResultsPanel: Examines the supplied experiment to determine the results destination and attempts to load the results.
setInstancesFromFile(File) - Method in class milk.gui.experiment.MIResultsPanel: Loads results from a set of instances contained in the supplied file.
setMaxC(double) - Method in class milk.visualize.SelectPanel
setMaxC(double) - Method in class milk.visualize.PlotPanel
setMaxC(double) - Method in class milk.visualize.MIPlot2D: Set the max color if the class is numeric
Before it's stored in m_maxC, it's stored in the tempory variable maxC.
setMaxIterations(int) - Method in class milk.classifiers.MIBoost: Set the maximum number of boost iterations
setMethod(int) - Method in class milk.classifiers.MIWrapper: Set the method used in testing.
setMinC(double) - Method in class milk.visualize.SelectPanel
setMinC(double) - Method in class milk.visualize.PlotPanel
setMinC(double) - Method in class milk.visualize.MIPlot2D: Set the min color if the class is numeric
Before it's stored in m_minC, it's stored in the tempory variable minC.
setNotes(String) - Method in class milk.experiment.MIRemoteExperiment: Set the user notes.
setNotes(String) - Method in class milk.experiment.MIExperiment: Set the user notes.
setNumClusters(int) - Method in class milk.classifiers.MIRBFNetwork: Set the Num_clusters value.
setNumFolds(int) - Method in class milk.experiment.MICrossValidationResultProducer: Set the value of NumFolds.
setOptions(String[]) - Method in class milk.classifiers.TLDSimple: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.TLD: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.SimpleMI: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MIWrapper: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MIRBFNetwork: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MINND: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MILRGEOM: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MILRARITH: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MILR: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MIBoost: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.MDD: Parses a given list of options.
setOptions(String[]) - Method in class milk.classifiers.DD: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MIRandomSplitResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MIInstanceQuery: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MIExperiment: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MICSVResultListener: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MICrossValidationResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class milk.experiment.MIClassifierSplitEvaluator: Parses a given list of options.
setOutputFile(File) - Method in class milk.experiment.MIRandomSplitResultProducer: Set the value of OutputFile.
setOutputFile(File) - Method in class milk.experiment.MICSVResultListener: Set the value of OutputFile.
setOutputFile(File) - Method in class milk.experiment.MICrossValidationResultProducer: Set the value of OutputFile.
setPlotExemplars(Exemplars) - Method in class milk.visualize.PlotPanel: Sets the exemplars to be plotted
setPlotExemplars(Exemplars) - Method in class milk.visualize.MIPlot2D: Sets the plot vectors from a set of exemplars
setPriors(Exemplars) - Method in class milk.classifiers.MIEvaluation: Sets the class prior probabilities
setProperty(int, Object) - Method in class milk.experiment.MIExperiment: Recursively sets the custom property value, by setting all values along the property path.
setPropertyArray(Object) - Method in class milk.experiment.MIRemoteExperiment: Sets the array of values to set the custom property to.
setPropertyArray(Object) - Method in class milk.experiment.MIExperiment: Sets the array of values to set the custom property to.
setPropertyPath(PropertyNode[]) - Method in class milk.experiment.MIRemoteExperiment: Sets the path of properties taken to get to the custom property to iterate over.
setPropertyPath(PropertyNode[]) - Method in class milk.experiment.MIExperiment: Sets the path of properties taken to get to the custom property to iterate over.
setQuery(String) - Method in class milk.experiment.MIInstanceQuery: Set the query to execute against the database
setRandomizeData(boolean) - Method in class milk.experiment.MIRandomSplitResultProducer: Set to true if dataset is to be randomized
setRawOutput(boolean) - Method in class milk.experiment.MIRandomSplitResultProducer: Set to true if raw split evaluator output is to be saved
setRawOutput(boolean) - Method in class milk.experiment.MICrossValidationResultProducer: Set to true if raw split evaluator output is to be saved
setRelationName(String) - Method in class milk.core.Exemplars: Sets the relation's name.
setResultKeyFromDialog() - Method in class milk.gui.experiment.MIResultsPanel
setResultListener(MIResultListener) - Method in interface milk.experiment.MIResultProducer: Sets the object to send results of each run to.
setResultListener(MIResultListener) - Method in class milk.experiment.MIRemoteExperiment: Sets the result listener where results will be sent.
setResultListener(MIResultListener) - Method in class milk.experiment.MIRandomSplitResultProducer: Sets the object to send results of each run to.
setResultListener(MIResultListener) - Method in class milk.experiment.MIExperiment: Sets the result listener where results will be sent.
setResultListener(MIResultListener) - Method in class milk.experiment.MICrossValidationResultProducer: Sets the object to send results of each run to.
setResultProducer(MIResultProducer) - Method in class milk.experiment.MIRemoteExperiment: Set the result producer used for the current experiment.
setResultProducer(MIResultProducer) - Method in class milk.experiment.MIExperiment: Set the result producer used for the current experiment.
setRidge(double) - Method in class milk.classifiers.MIRBFNetwork: Set the Ridge value.
setRidge(double) - Method in class milk.classifiers.MILRGEOM: Sets the ridge in the log-likelihood.
setRidge(double) - Method in class milk.classifiers.MILRARITH: Sets the ridge in the log-likelihood.
setRidge(double) - Method in class milk.classifiers.MILR: Sets the ridge in the log-likelihood.
setRunLower(int) - Method in class milk.experiment.MIRemoteExperiment: Set the lower run number for the experiment.
setRunLower(int) - Method in class milk.experiment.MIExperiment: Set the lower run number for the experiment.
setRunUpper(int) - Method in class milk.experiment.MIRemoteExperiment: Set the upper run number for the experiment.
setRunUpper(int) - Method in class milk.experiment.MIExperiment: Set the upper run number for the experiment.
setSparseData(boolean) - Method in class milk.experiment.MIInstanceQuery: Sets whether data should be encoded as sparse instances
setSplitByDataSet(boolean) - Method in class milk.experiment.MIRemoteExperiment: Set whether sub experiments are to be created on the basis of data set.
setSplitEvaluator(MISplitEvaluator) - Method in class milk.experiment.MIRandomSplitResultProducer: Set the SplitEvaluator.
setSplitEvaluator(MISplitEvaluator) - Method in class milk.experiment.MICrossValidationResultProducer: Set the SplitEvaluator.
setStdDev(double) - Method in class milk.visualize.PlotPanel
setStdDev(double) - Method in class milk.visualize.DistributionPanel
setTestBaseFromDialog() - Method in class milk.gui.experiment.MIResultsPanel
setTrainPercent(double) - Method in class milk.experiment.MIRandomSplitResultProducer: Set the value of TrainPercent.
setTransformMethod(int) - Method in class milk.classifiers.SimpleMI: Set the method used in transformation.
setTTester() - Method in class milk.gui.experiment.MIResultsPanel: Updates the test chooser with possible tests
setUsePropertyIterator(boolean) - Method in class milk.experiment.MIRemoteExperiment: Sets whether the custom property iterator should be used.
setUsePropertyIterator(boolean) - Method in class milk.experiment.MIExperiment: Sets whether the custom property iterator should be used.
setWeight(double) - Method in class milk.core.Exemplar: Sets the weight of the exemplar.
setX(Axis) - Method in class milk.visualize.MIPlot2D: Set the index and value of the attribute to go on the x axis
Before it's stored in m_xIndex, m_maxX and m_minX, it's stored in the tempory variable x.
setXIndex(int) - Method in class milk.visualize.GeomPanel: Set the x axis, then it fire the property change event to inform (the MIPlot) that the x axis changes
setXIndex(int) - Method in class milk.visualize.DistributionPanel
setXValue(Axis) - Method in class milk.visualize.PlotPanel: Set the index of the attribute to go on the x axis
setY(Axis) - Method in class milk.visualize.MIPlot2D: Set the index and value of the attribute to go on the y axis
Before it's stored in m_yIndex, m_maxY and m_minY, it's stored in the tempory variable y.
setYIndex(int) - Method in class milk.visualize.GeomPanel: Set the y axis, then it fire the property change event to inform (the MIPlot) that the y axis changes
SimpleMI - class milk.classifiers.SimpleMI.: Avg of feature data and reduce MI data into mono-instance Valid options are:
SimpleMI() - Constructor for class milk.classifiers.SimpleMI
SOME_OTHER_FAILURE - Static variable in class milk.experiment.MIRemoteExperiment
sort() - Method in class milk.core.Exemplars: Sorts the instances based on the ID attribute.
sparseDataTipText() - Method in class milk.experiment.MIInstanceQuery: Returns the tip text for this property
splitEvaluatorTipText() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the tip text for this property
splitEvaluatorTipText() - Method in class milk.experiment.MICrossValidationResultProducer: Returns the tip text for this property
statusMessage(String) - Method in class milk.gui.experiment.MIRunPanel: Sends the supplied message to the log panel status line.
stdDev - Variable in class milk.visualize.PlotPanel: The std.
stratify(int) - Method in class milk.core.Exemplars: Stratifies a set of exemplars according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
sumsOfWeights() - Method in class milk.core.Exemplars: Computes the sum of all the exemplars' weights.

T

tableExists(String) - Method in class milk.experiment.MIDatabaseUtils: Checks that a given table exists.
target(double[], double[][], int, double[]) - Method in class milk.classifiers.MINND: Compute the target function to minimize in gradient descent The formula is:
1/2*sum[i=1..p](f(X, Xi)-var(Y, Yi))^2
testCV(int, int) - Method in class milk.core.Exemplars: Creates the test set for one fold of a cross-validation on the dataset.
TIMESTAMP_FIELD_NAME - Static variable in class milk.experiment.MIRandomSplitResultProducer
TIMESTAMP_FIELD_NAME - Static variable in class milk.experiment.MICrossValidationResultProducer
TLD - class milk.classifiers.TLD.: 0657.594 Thesis Two-Level Distribution approach, changes the starting value of the searching algorithm, supplement the cut-off modification and check missing values.
TLD() - Constructor for class milk.classifiers.TLD
TLDData - class milk.data.TLDData.: Generate n-dimensional 2-class MI data using two level distributions prior = 0.5
TLDData() - Constructor for class milk.data.TLDData
TLDSimple - class milk.classifiers.TLDSimple.: 0657.594 Thesis A simpler version of TLD, \mu random but \sigma^2 fixed and estimated via data
TLDSimple() - Constructor for class milk.classifiers.TLDSimple
TLDSimpleData - class milk.data.TLDSimpleData.: Generate n-dimensional 2-class MI data using two level distributions, Simpler version prior = 0.5
TLDSimpleData() - Constructor for class milk.data.TLDSimpleData
toClassDetailsString() - Method in class milk.classifiers.MIEvaluation
toClassDetailsString(String) - Method in class milk.classifiers.MIEvaluation: Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toMatrixString() - Method in class milk.classifiers.MIEvaluation: Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class milk.classifiers.MIEvaluation: Outputs the performance statistics as a classification confusion matrix.
toString() - Method in class milk.classifiers.TLDSimple: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.SimpleMI: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MIWrapper: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MIRBFNetwork: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MILRGEOM: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MILRARITH: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MILR: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MIBoost: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.MDD: Gets a string describing the classifier.
toString() - Method in class milk.classifiers.DD: Gets a string describing the classifier.
toString() - Method in class milk.core.Exemplars: Returns the exemplars as a string.
toString() - Method in class milk.core.Exemplar: Returns the exemplar as a string.
toString() - Method in class milk.experiment.MIRemoteExperiment: Overides toString in Experiment
toString() - Method in class milk.experiment.MIRandomSplitResultProducer: Gets a text descrption of the result producer.
toString() - Method in class milk.experiment.MIExperiment: Gets a string representation of the experiment configuration.
toString() - Method in class milk.experiment.MICrossValidationResultProducer: Gets a text descrption of the result producer.
toString() - Method in class milk.experiment.MIClassifierSplitEvaluator: Returns a text description of the split evaluator.
toSummaryString() - Method in class milk.classifiers.MIEvaluation: Calls toSummaryString() with no title and no complexity stats
toSummaryString(boolean) - Method in class milk.classifiers.MIEvaluation: Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class milk.classifiers.MIEvaluation: Outputs the performance statistics in summary form.
totalCost() - Method in class milk.classifiers.MIEvaluation: Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
trainCV(int, int) - Method in class milk.core.Exemplars: Creates the training set skipping for one fold of a cross-validation on the exemplar set.
trainCV(int, int, Random) - Method in class milk.core.Exemplars: Creates the training set for one fold of a cross-validation on the dataset.
trainPercentTipText() - Method in class milk.experiment.MIRandomSplitResultProducer: Returns the tip text for this property
transform(Exemplar) - Method in class milk.classifiers.MIRBFNetwork
transform(Exemplars) - Method in class milk.classifiers.SimpleMI
transform(Exemplars) - Method in class milk.classifiers.MIWrapper
transform(Exemplars) - Method in interface milk.classifiers.MITransform: transform the given exemplars to an Instances object.
transform(Exemplars) - Method in class milk.classifiers.MIRBFNetwork
trueNegativeRate(int) - Method in class milk.classifiers.MIEvaluation: Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class milk.classifiers.MIEvaluation: Calculate the true positive rate with respect to a particular class.
typeName(int) - Static method in class milk.experiment.MIDatabaseUtils: Returns the name associated with a SQL type.

U

unclassified() - Method in class milk.classifiers.MIEvaluation: Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
updateClassifier(Exemplar) - Method in interface milk.classifiers.MIUpdateableClassifier: Updates a classifier using the given exemplar.
updateOptions() - Method in class milk.experiment.MIClassifierSplitEvaluator: Updates the options that the current classifier is using.
updatePriors(Exemplar) - Method in class milk.classifiers.MIEvaluation: Updates the class prior probabilities (when incrementally training)
updateResultsTableName(MIResultProducer) - Method in class milk.experiment.MIDatabaseResultListener: Determines the table name that results will be inserted into.

V

variance() - Method in class milk.core.Exemplar: Computes the variances for all numeric attributes.

W

waitingExperiment(int) - Method in class milk.experiment.MIRemoteExperiment: Push an experiment back on the queue of waiting experiments
weight() - Method in class milk.core.Exemplar: Returns the exemplar's weight.
wekaStaticWrapper(Sourcable, String) - Static method in class milk.classifiers.MIEvaluation: Wraps a static classifier in enough source to test using the weka class libraries.

X

x - Variable in class milk.visualize.PlotPanel: Indexes of the attributes to go on the x axis
x - Variable in class milk.visualize.MIPlot2D: The x and y axis, max and min values are of all the exemplars
xMean - Variable in class milk.classifiers.MILRGEOM
xMean - Variable in class milk.classifiers.MILRARITH
xSD - Variable in class milk.classifiers.MILRGEOM
xSD - Variable in class milk.classifiers.MILRARITH

Y

y - Variable in class milk.visualize.MIPlot2D: The x and y axis, max and min values are of all the exemplars

Z

ZERO - Static variable in class milk.classifiers.TLDSimple: The very small number representing zero
ZERO - Static variable in class milk.classifiers.TLD: The very small number representing zero

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