# Serialized Form

Package milk.classifiers

Class milk.classifiers.DD implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Par

    double[] m_Par

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Data

    double[][][] m_Data

  MI data

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

Class milk.classifiers.MDD implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Par

    double[] m_Par

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Data

    double[][][] m_Data

  MI data

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

### m_Seed

    long m_Seed

Class milk.classifiers.MIBoost implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Models

    weka.classifiers.Classifier[] m_Models

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

### m_NumIterations

    int m_NumIterations

  Number of iterations

### m_Classifier

    weka.classifiers.Classifier m_Classifier

  The model base classifier to use

### m_Beta

    double[] m_Beta

  Voting weights of models

### m_MaxIterations

    int m_MaxIterations

### m_DiscretizeBin

    int m_DiscretizeBin

### m_Filter

    weka.filters.unsupervised.attribute.Discretize m_Filter

Class milk.classifiers.MIClassifier implements Serializable

Class milk.classifiers.MILR implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Par

    double[] m_Par

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Ridge

    double m_Ridge

  The ridge parameter.

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Data

    double[][][] m_Data

  MI data

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

Class milk.classifiers.MILRARITH implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Par

    double[] m_Par

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Ridge

    double m_Ridge

  The ridge parameter.

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Data

    double[][][] m_Data

  MI data

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

### xMean

    double[] xMean

### xSD

    double[] xSD

Class milk.classifiers.MILRGEOM implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_Par

    double[] m_Par

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Ridge

    double m_Ridge

  The ridge parameter.

### m_Debug

    boolean m_Debug

  Debugging output

### m_Classes

    int[] m_Classes

  Class labels for each bag

### m_Data

    double[][][] m_Data

  MI data

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

### xMean

    double[] xMean

### xSD

    double[] xSD

Class milk.classifiers.MINND implements Serializable

Serialized Fields

### m_Neighbour

    int m_Neighbour

  The number of nearest neighbour for prediction

### m_Mean

    double[][] m_Mean

  The mean for each attribute of each exemplar

### m_Variance

    double[][] m_Variance

  The variance for each attribute of each exemplar

### m_Dimension

    int m_Dimension

  The dimension of each exemplar, i.e. (numAttributes-2)

### m_Class

    double[] m_Class

  The class label of each exemplar

### m_NumClasses

    int m_NumClasses

  The number of class labels in the data

### m_Weights

    double[] m_Weights

  The weight of each exemplar

### m_Rate

    double m_Rate

  The learning rate in the gradient descent

### m_MinArray

    double[] m_MinArray

  The minimum values for numeric attributes.

### m_MaxArray

    double[] m_MaxArray

  The maximum values for numeric attributes.

### m_STOP

    double m_STOP

  The stopping criteria of gradient descent

### m_Change

    double[][] m_Change

  The weights that alter the dimnesion of each exemplar

### m_NoiseM

    double[][] m_NoiseM

  The noise data of each exemplar

### m_NoiseV

    double[][] m_NoiseV

  The noise data of each exemplar

### m_ValidM

    double[][] m_ValidM

  The noise data of each exemplar

### m_ValidV

    double[][] m_ValidV

  The noise data of each exemplar

### m_Select

    int m_Select

  The number of nearest neighbour instances in the selection of noises in the training data

### m_Choose

    int m_Choose

  The number of nearest neighbour exemplars in the selection of noises in the test data

### m_ClassIndex

    int m_ClassIndex

  The class and ID attribute index of the data

### m_IdIndex

    int m_IdIndex

  The class and ID attribute index of the data

### m_Decay

    double m_Decay

  The decay rate of learning rate

Class milk.classifiers.MIRBFNetwork implements Serializable

Serialized Fields

### m_logistic

    MIClassifier m_logistic

  The logistic regression model

### m_clm

    weka.filters.unsupervised.attribute.ClusterMembership m_clm

  The RBF filter

### m_num_clusters

    int m_num_clusters

  The number of clusters to use

### m_ridge

    double m_ridge

  The ridge regression coefficient for logistic regression

Class milk.classifiers.MIWrapper implements Serializable

Serialized Fields

### m_ClassIndex

    int m_ClassIndex

  The index of the class attribute

### m_NumClasses

    int m_NumClasses

  The number of the class labels

### m_IdIndex

    int m_IdIndex

### m_Debug

    boolean m_Debug

  Debugging output

### m_Attributes

    weka.core.Instances m_Attributes

  All attribute names

### m_Classifier

    weka.classifiers.Classifier m_Classifier

### m_Method

    int m_Method

Class milk.classifiers.SimpleMI implements Serializable

Serialized Fields

### m_TransformMethod

    int m_TransformMethod

### m_Exemplars

    Exemplars m_Exemplars

Class milk.classifiers.TLD implements Serializable

Serialized Fields

### m_MeanP

    double[][] m_MeanP

  The mean for each attribute of each positive exemplar

### m_VarianceP

    double[][] m_VarianceP

  The variance for each attribute of each positive exemplar

### m_MeanN

    double[][] m_MeanN

  The mean for each attribute of each negative exemplar

### m_VarianceN

    double[][] m_VarianceN

  The variance for each attribute of each negative exemplar

### m_SumP

    double[][] m_SumP

  The effective sum of weights of each positive exemplar in each dimension

### m_SumN

    double[][] m_SumN

  The effective sum of weights of each negative exemplar in each dimension

### m_ParamsP

    double[] m_ParamsP

  The parameters to be estimated for each positive exemplar

### m_ParamsN

    double[] m_ParamsN

  The parameters to be estimated for each negative exemplar

### m_Dimension

    int m_Dimension

  The dimension of each exemplar, i.e. (numAttributes-2)

### m_Class

    double[] m_Class

  The class label of each exemplar

### m_NumClasses

    int m_NumClasses

  The number of class labels in the data

### m_ClassIndex

    int m_ClassIndex

  The class and ID attribute index of the data

### m_IdIndex

    int m_IdIndex

  The class and ID attribute index of the data

### m_Run

    int m_Run

### m_Seed

    long m_Seed

### m_Cutoff

    double m_Cutoff

### m_UseEmpiricalCutOff

    boolean m_UseEmpiricalCutOff

Class milk.classifiers.TLDSimple implements Serializable

Serialized Fields

### m_MeanP

    double[][] m_MeanP

  The mean for each attribute of each positive exemplar

### m_MeanN

    double[][] m_MeanN

  The mean for each attribute of each negative exemplar

### m_SumP

    double[][] m_SumP

  The effective sum of weights of each positive exemplar in each dimension

### m_SumN

    double[][] m_SumN

  The effective sum of weights of each negative exemplar in each dimension

### m_SgmSqP

    double[] m_SgmSqP

  Estimated sigma^2 in positive bags

### m_SgmSqN

    double[] m_SgmSqN

  Estimated sigma^2 in negative bags

### m_ParamsP

    double[] m_ParamsP

  The parameters to be estimated for each positive exemplar

### m_ParamsN

    double[] m_ParamsN

  The parameters to be estimated for each negative exemplar

### m_Dimension

    int m_Dimension

  The dimension of each exemplar, i.e. (numAttributes-2)

### m_Class

    double[] m_Class

  The class label of each exemplar

### m_NumClasses

    int m_NumClasses

  The number of class labels in the data

### m_ClassIndex

    int m_ClassIndex

  The class and ID attribute index of the data

### m_IdIndex

    int m_IdIndex

  The class and ID attribute index of the data

### m_Run

    int m_Run

### m_Seed

    long m_Seed

### m_Cutoff

    double m_Cutoff

### m_UseEmpiricalCutOff

    boolean m_UseEmpiricalCutOff

### m_LkRatio

    double[] m_LkRatio

### m_Attribute

    weka.core.Instances m_Attribute

Package milk.core

Class milk.core.Exemplar implements Serializable

Serialized Fields

### m_IdIndex

    int m_IdIndex

  The exemplar's ID attribute

### m_IdValue

    double m_IdValue

  The value of the ID of this exemplar

### m_ClassIndex

    int m_ClassIndex

  The class index of this exemplar

### m_ClassValue

    double m_ClassValue

  The class value of this exemplar

### m_Instances

    weka.core.Instances m_Instances

  The instances in the exemplar

### m_Weight

    double m_Weight

  The weight of this exemplar

Class milk.core.Exemplars implements Serializable

Serialized Fields

### m_RelationName

    java.lang.String m_RelationName

  The dataset's name.

### m_Attributes

    weka.core.Attribute[] m_Attributes

  The attribute information.

### m_Exemplars

    java.util.Vector m_Exemplars

  The exemplars.

### m_IdIndex

    int m_IdIndex

  The exemplars' ID attribute

### m_ClassIndex

    int m_ClassIndex

  The class index of this exemplar

Package milk.experiment

Class milk.experiment.MIClassifierSplitEvaluator implements Serializable

Serialized Fields

### m_Classifier

    MIClassifier m_Classifier

  The classifier used for evaluation

### m_AdditionalMeasures

    java.lang.String[] m_AdditionalMeasures

  The names of any additional measures to look for in SplitEvaluators

### m_doesProduce

    boolean[] m_doesProduce

  Array of booleans corresponding to the measures in m_AdditionalMeasures indicating which of the AdditionalMeasures the current classifier can produce

### m_numberAdditionalMeasures

    int m_numberAdditionalMeasures

  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_result

    java.lang.String m_result

  Holds the statistics for the most recent application of the classifier

### m_ClassifierOptions

    java.lang.String m_ClassifierOptions

  The classifier options (if any)

### m_ClassifierVersion

    java.lang.String m_ClassifierVersion

  The classifier version

### m_IRclass

    int m_IRclass

  Class index for information retrieval statistics (default 0)

Class milk.experiment.MICrossValidationResultProducer implements Serializable

Serialized Fields

### m_Instances

    Exemplars m_Instances

  The dataset of interest

### m_ResultListener

    MIResultListener m_ResultListener

  The ResultListener to send results to

### m_NumFolds

    int m_NumFolds

  The number of folds in the cross-validation

### m_debugOutput

    boolean m_debugOutput

  Save raw output of split evaluators --- for debugging purposes

### m_ZipDest

    weka.experiment.OutputZipper m_ZipDest

  The output zipper to use for saving raw splitEvaluator output

### m_OutputFile

    java.io.File m_OutputFile

  The destination output file/directory for raw output

### m_SplitEvaluator

    MISplitEvaluator m_SplitEvaluator

  The SplitEvaluator used to generate results

### m_AdditionalMeasures

    java.lang.String[] m_AdditionalMeasures

  The names of any additional measures to look for in SplitEvaluators

Class milk.experiment.MICSVResultListener implements Serializable

Serialized Fields

### m_RP

    MIResultProducer m_RP

  The MIResultProducer sending us results

### m_OutputFile

    java.io.File m_OutputFile

  The destination output file, null sends to System.out

Class milk.experiment.MIDatabaseResultListener implements Serializable

Serialized Fields

### m_ResultProducer

    MIResultProducer m_ResultProducer

  The ResultProducer to listen to

### m_ResultsTableName

    java.lang.String m_ResultsTableName

  The name of the current results table

### m_Debug

    boolean m_Debug

  True if debugging output should be printed

### m_CacheKeyName

    java.lang.String m_CacheKeyName

  Holds the name of the key field to cache upon, or null if no caching

### m_CacheKeyIndex

    int m_CacheKeyIndex

  Stores the index of the key column holding the cache key data

### m_CacheKey

    java.lang.Object[] m_CacheKey

  Stores the key for which the cache is valid

### m_Cache

    weka.core.FastVector m_Cache

  Stores the cached values

Class milk.experiment.MIDatabaseUtils implements Serializable

Serialized Fields

### m_DatabaseURL

    java.lang.String m_DatabaseURL

  Database URL

### m_Connection

    java.sql.Connection m_Connection

  The database connection

### m_Statement

    java.sql.Statement m_Statement

  The statement used for database queries

### m_Debug

    boolean m_Debug

  True if debugging output should be printed

Class milk.experiment.MIExperiment implements Serializable

Serialized Fields

### m_ResultListener

    MIResultListener m_ResultListener

  Where results will be sent

### m_ResultProducer

    MIResultProducer m_ResultProducer

  The result producer

### m_RunLower

    int m_RunLower

  Lower run number

### m_RunUpper

    int m_RunUpper

  Upper run number

### m_Datasets

    javax.swing.DefaultListModel m_Datasets

  An array of dataset files

### m_UsePropertyIterator

    boolean m_UsePropertyIterator

  True if the exp should also iterate over a property of the RP

### m_PropertyPath

    weka.experiment.PropertyNode[] m_PropertyPath

  The path to the iterator property

### m_PropertyArray

    java.lang.Object m_PropertyArray

  The array of values to set the property to

### m_Notes

    java.lang.String m_Notes

  User notes about the experiment

### m_AdditionalMeasures

    java.lang.String[] m_AdditionalMeasures

  Method names of additional measures of objects contained in the custom property iterator. Only methods names beginning with "measure" and returning doubles are recognised

### m_ClassFirst

    boolean m_ClassFirst

  True if the class attribute is the first attribute for all datasets involved in this experiment.

### m_AdvanceDataSetFirst

    boolean m_AdvanceDataSetFirst

  If true an experiment will advance the current data set befor any custom itererator

### m_m_AdvanceRunFirst

    boolean m_m_AdvanceRunFirst

Class milk.experiment.MIInstanceQuery implements Serializable

Serialized Fields

### m_CreateSparseData

    boolean m_CreateSparseData

  Determines whether sparse data is created

### m_Query

    java.lang.String m_Query

  Query to execute

Class milk.experiment.MIInstancesResultListener implements Serializable

Class milk.experiment.MIRandomSplitResultProducer implements Serializable

Serialized Fields

### m_Instances

    Exemplars m_Instances

  The dataset of interest

### m_ResultListener

    MIResultListener m_ResultListener

  The ResultListener to send results to

### m_TrainPercent

    double m_TrainPercent

  The percentage of instances to use for training

### m_randomize

    boolean m_randomize

  Whether dataset is to be randomized

### m_SplitEvaluator

    MISplitEvaluator m_SplitEvaluator

  The SplitEvaluator used to generate results

### m_AdditionalMeasures

    java.lang.String[] m_AdditionalMeasures

  The names of any additional measures to look for in SplitEvaluators

### m_debugOutput

    boolean m_debugOutput

  Save raw output of split evaluators --- for debugging purposes

### m_ZipDest

    weka.experiment.OutputZipper m_ZipDest

  The output zipper to use for saving raw splitEvaluator output

### m_OutputFile

    java.io.File m_OutputFile

  The destination output file/directory for raw output

Class milk.experiment.MIRemoteExperiment implements Serializable

Serialized Fields

### m_listeners

    weka.core.FastVector m_listeners

  The list of objects listening for remote experiment events

### m_remoteHosts

    javax.swing.DefaultListModel m_remoteHosts

  Holds the names of machines with remoteEngine servers running

### m_remoteHostsQueue

    weka.core.Queue m_remoteHostsQueue

  The queue of available hosts

### m_remoteHostsStatus

    int[] m_remoteHostsStatus

  The status of each of the remote hosts

### m_remoteHostFailureCounts

    int[] m_remoteHostFailureCounts

  The number of times tasks have failed on each remote host

### m_experimentAborted

    boolean m_experimentAborted

  Set to true if MAX_FAILURES exceeded on all hosts or connections fail on all hosts or user aborts experiment (via gui)

### m_removedHosts

    int m_removedHosts

  The number of hosts removed due to exceeding max failures

### m_failedCount

    int m_failedCount

  The count of failed sub-experiments

### m_finishedCount

    int m_finishedCount

  The count of successfully completed sub-experiments

### m_baseExperiment

    MIExperiment m_baseExperiment

  The base experiment to split up into sub experiments for remote execution

### m_subExperiments

    MIExperiment[] m_subExperiments

  The sub experiments

### m_subExpQueue

    weka.core.Queue m_subExpQueue

  The queue of sub experiments waiting to be processed

### m_subExpComplete

    int[] m_subExpComplete

  The status of each of the sub-experiments

### m_splitByDataSet

    boolean m_splitByDataSet

  If true, then sub experiments are created on the basis of data sets rather than run number.

Class milk.experiment.MIRemoteExperimentSubTask implements Serializable

Serialized Fields

### m_result

    weka.experiment.TaskStatusInfo m_result

### m_experiment

    MIExperiment m_experiment

Package milk.gui.experiment

Class milk.gui.experiment.MIDatasetListPanel implements Serializable

Serialized Fields

### m_Exp

    MIExperiment m_Exp

  The experiment to set the dataset list of

### m_List

    javax.swing.JList m_List

  The component displaying the dataset list

### m_AddBut

    javax.swing.JButton m_AddBut

  Click to add a dataset

### m_DeleteBut

    javax.swing.JButton m_DeleteBut

  Click to remove the selected dataset from the list

### m_relativeCheck

    javax.swing.JCheckBox m_relativeCheck

  Make file paths relative to the user (start) directory

### m_ArffFilter

    javax.swing.filechooser.FileFilter m_ArffFilter

  A filter to ensure only arff files get selected

### m_UserDir

    java.io.File m_UserDir

  The user (start) directory

### m_FileChooser

    javax.swing.JFileChooser m_FileChooser

  The file chooser component

Class milk.gui.experiment.MIDistributeExperimentPanel implements Serializable

Serialized Fields

### m_Exp

    MIRemoteExperiment m_Exp

  The experiment to configure.

### m_enableDistributedExperiment

    javax.swing.JCheckBox m_enableDistributedExperiment

  Distribute the current experiment to remote hosts

### m_configureHostNames

    javax.swing.JButton m_configureHostNames

  Popup the HostListPanel

### m_hostList

    MIHostListPanel m_hostList

  The host list panel

### m_splitByDataSet

    javax.swing.JRadioButton m_splitByDataSet

  Split experiment up by data set.

### m_splitByRun

    javax.swing.JRadioButton m_splitByRun

  Split experiment up by run number.

### m_radioListener

    java.awt.event.ActionListener m_radioListener

  Handle radio buttons

Class milk.gui.experiment.MIExperimenter implements Serializable

Serialized Fields

### m_SetupPanel

    MISetupPanel m_SetupPanel

  The panel for configuring the experiment

### m_RunPanel

    MIRunPanel m_RunPanel

  The panel for running the experiment

### m_ResultsPanel

    MIResultsPanel m_ResultsPanel

  The panel for analysing experimental results

### m_TabbedPane

    javax.swing.JTabbedPane m_TabbedPane

  The tabbed pane that controls which sub-pane we are working with

### m_ClassFirst

    boolean m_ClassFirst

  True if the class attribute is the first attribute for all datasets involved in this experiment.

Class milk.gui.experiment.MIGeneratorPropertyIteratorPanel implements Serializable

Serialized Fields

### m_ConfigureBut

    javax.swing.JButton m_ConfigureBut

  Click to select the property to iterate over

### m_StatusBox

    javax.swing.JComboBox m_StatusBox

  Controls whether the custom iterator is used or not

### m_ArrayEditor

    weka.gui.GenericArrayEditor m_ArrayEditor

  Allows editing of the custom property values

### m_Exp

    MIExperiment m_Exp

  The experiment this all applies to

### m_Listeners

    weka.core.FastVector m_Listeners

  Listeners who want to be notified about editing status of this panel

Class milk.gui.experiment.MIHostListPanel implements Serializable

Serialized Fields

### m_Exp

    MIRemoteExperiment m_Exp

  The remote experiment to set the host list of

### m_List

    javax.swing.JList m_List

  The component displaying the host list

### m_DeleteBut

    javax.swing.JButton m_DeleteBut

  Click to remove the selected host from the list

### m_HostField

    javax.swing.JTextField m_HostField

  The field with which to enter host names

Class milk.gui.experiment.MIResultsPanel implements Serializable

Serialized Fields

### m_FromFileBut

    javax.swing.JButton m_FromFileBut

  Click to load results from a file

### m_FromDBaseBut

    javax.swing.JButton m_FromDBaseBut

  Click to load results from a database

### m_FromExpBut

    javax.swing.JButton m_FromExpBut

  Click to get results from the destination given in the experiment

### m_FromLab

    javax.swing.JLabel m_FromLab

  Displays a message about the current result set

### m_DatasetModel

    javax.swing.DefaultComboBoxModel m_DatasetModel

  The model embedded in m_DatasetCombo

### m_RunModel

    javax.swing.DefaultComboBoxModel m_RunModel

  The model embedded in m_RunCombo

### m_CompareModel

    javax.swing.DefaultComboBoxModel m_CompareModel

  The model embedded in m_CompareCombo

### m_TestsModel

    javax.swing.DefaultListModel m_TestsModel

  The model embedded in m_TestsList

### m_DatasetKeyLabel

    javax.swing.JLabel m_DatasetKeyLabel

  Displays the currently selected column names for the scheme & options

### m_DatasetKeyBut

    javax.swing.JButton m_DatasetKeyBut

  Click to edit the columns used to determine the scheme

### m_DatasetKeyModel

    javax.swing.DefaultListModel m_DatasetKeyModel

  Stores the list of attributes for selecting the scheme columns

### m_DatasetKeyList

    javax.swing.JList m_DatasetKeyList

  Displays the list of selected columns determining the scheme

### m_RunCombo

    javax.swing.JComboBox m_RunCombo

  Lets the user select which column contains the run number

### m_ResultKeyLabel

    javax.swing.JLabel m_ResultKeyLabel

  Displays the currently selected column names for the scheme & options

### m_ResultKeyBut

    javax.swing.JButton m_ResultKeyBut

  Click to edit the columns used to determine the scheme

### m_ResultKeyModel

    javax.swing.DefaultListModel m_ResultKeyModel

  Stores the list of attributes for selecting the scheme columns

### m_ResultKeyList

    javax.swing.JList m_ResultKeyList

  Displays the list of selected columns determining the scheme

### m_TestsButton

    javax.swing.JButton m_TestsButton

  Lets the user select which scheme to base comparisons against

### m_TestsList

    javax.swing.JList m_TestsList

  Holds the list of schemes to base the test against

### m_CompareCombo

    javax.swing.JComboBox m_CompareCombo

  Lets the user select which performance measure to analyze

### m_SigTex

    javax.swing.JTextField m_SigTex

  Lets the user edit the test significance

### m_ShowStdDevs

    javax.swing.JCheckBox m_ShowStdDevs

  Lets the user select whether standard deviations are to be output or not

### m_PerformBut

    javax.swing.JButton m_PerformBut

  Click to start the test

### m_SaveOutBut

    javax.swing.JButton m_SaveOutBut

  Click to save test output to a file

### m_SaveOut

    weka.gui.SaveBuffer m_SaveOut

  The buffer saving object for saving output

### m_OutText

    javax.swing.JTextArea m_OutText

  Displays the output of tests

### m_History

    weka.gui.ResultHistoryPanel m_History

  A panel controlling results viewing

### m_ArffFilter

    javax.swing.filechooser.FileFilter m_ArffFilter

  Filter to ensure only arff files are selected for result files

### m_FileChooser

    javax.swing.JFileChooser m_FileChooser

  The file chooser for selecting result files

### m_TTester

    weka.experiment.PairedTTester m_TTester

  The PairedTTester object

### m_Instances

    weka.core.Instances m_Instances

  The instances we're extracting results from

### m_InstanceQuery

    MIInstanceQuery m_InstanceQuery

  Does any database querying for us

### m_LoadThread

    java.lang.Thread m_LoadThread

  A thread to load results instances from a file or database

### m_Exp

    MIExperiment m_Exp

  An experiment (used for identifying a result source) -- optional

### m_ConfigureListener

    java.awt.event.ActionListener m_ConfigureListener

  An actionlisteners that updates ttest settings

### COMBO_SIZE

    java.awt.Dimension COMBO_SIZE

Class milk.gui.experiment.MIRunNumberPanel implements Serializable

Serialized Fields

### m_LowerText

    javax.swing.JTextField m_LowerText

  Configures the lower run number

### m_UpperText

    javax.swing.JTextField m_UpperText

  Configures the upper run number

### m_Exp

    MIExperiment m_Exp

  The experiment being configured

Class milk.gui.experiment.MIRunPanel implements Serializable

Serialized Fields

### m_StartBut

    javax.swing.JButton m_StartBut

  Click to start running the experiment

### m_StopBut

    javax.swing.JButton m_StopBut

  Click to signal the running experiment to halt

### m_Log

    weka.gui.LogPanel m_Log

### m_Exp

    MIExperiment m_Exp

  The experiment to run

### m_RunThread

    java.lang.Thread m_RunThread

  The thread running the experiment

Class milk.gui.experiment.MISetupPanel implements Serializable

Serialized Fields

### m_Exp

    MIExperiment m_Exp

  The experiment being configured

### m_OpenBut

    javax.swing.JButton m_OpenBut

  Click to load an experiment

### m_SaveBut

    javax.swing.JButton m_SaveBut

  Click to save an experiment

### m_NewBut

    javax.swing.JButton m_NewBut

  Click to create a new experiment with default settings

### m_ExpFilter

    javax.swing.filechooser.FileFilter m_ExpFilter

  A filter to ensure only experiment files get shown in the chooser

### m_FileChooser

    javax.swing.JFileChooser m_FileChooser

  The file chooser for selecting experiments

### m_RPEditor

    weka.gui.GenericObjectEditor m_RPEditor

  The ResultProducer editor

### m_RPEditorPanel

    weka.gui.PropertyPanel m_RPEditorPanel

  The panel to contain the ResultProducer editor

### m_RLEditor

    weka.gui.GenericObjectEditor m_RLEditor

  The ResultListener editor

### m_RLEditorPanel

    weka.gui.PropertyPanel m_RLEditorPanel

  The panel to contain the ResultListener editor

### m_GeneratorPropertyPanel

    MIGeneratorPropertyIteratorPanel m_GeneratorPropertyPanel

  The panel that configures iteration on custom resultproducer property

### m_RunNumberPanel

    MIRunNumberPanel m_RunNumberPanel

  The panel for configuring run numbers

### m_DistributeExperimentPanel

    MIDistributeExperimentPanel m_DistributeExperimentPanel

  The panel for enabling a distributed experiment

### m_DatasetListPanel

    MIDatasetListPanel m_DatasetListPanel

  The panel for configuring selected datasets

### m_NotesText

    javax.swing.JTextArea m_NotesText

  Area for user notes Default of 5 rows

### m_Support

    java.beans.PropertyChangeSupport m_Support

  Manages sending notifications to people when we change the experiment, at this stage, only the resultlistener so the resultpanel can update.

### m_advanceDataSetFirst

    javax.swing.JRadioButton m_advanceDataSetFirst

  Click to advacne data set before custom generator

### m_advanceIteratorFirst

    javax.swing.JRadioButton m_advanceIteratorFirst

  Click to advance custom generator before data set

### m_RadioListener

    java.awt.event.ActionListener m_RadioListener

  Handle radio buttons

Package milk.visualize

Class milk.visualize.DistributionPanel implements Serializable

Serialized Fields

### stdDev

    double stdDev

### xIndex

    Axis xIndex

### xAttr

    javax.swing.JComboBox xAttr

### sd

    javax.swing.JTextField sd

### sdlbl

    javax.swing.JLabel sdlbl

### sdpnl

    javax.swing.JPanel sdpnl

### select

    SelectPanel select

### plot

    PlotPanel plot

Class milk.visualize.GeomPanel implements Serializable

Serialized Fields

### xIndex

    Axis xIndex

### yIndex

    Axis yIndex

### xAttr

    javax.swing.JComboBox xAttr

### yAttr

    javax.swing.JComboBox yAttr

### select

    SelectPanel select

### plot

    MIPlot2D plot

Class milk.visualize.MIExplorer implements Serializable

Serialized Fields

### m_PreprocessPanel

    weka.gui.explorer.PreprocessPanel m_PreprocessPanel

  The panel for preprocessing instances

### m_DistributionPanel

    DistributionPanel m_DistributionPanel

  The panel to show distributions

### m_GeomPanel

    GeomPanel m_GeomPanel

  The panel to show data geometrically

### m_TabbedPane

    javax.swing.JTabbedPane m_TabbedPane

  The tabbed pane that controls which sub-pane we are working with

### m_LogPanel

    weka.gui.LogPanel m_LogPanel

  The panel for log and status messages

Class milk.visualize.MIPanel implements Serializable

Serialized Fields

### exemplars

    Exemplars exemplars

### cp

    weka.gui.visualize.ClassPanel cp

### insts

    weka.core.Instances insts

### ip

    javax.swing.JPanel ip

### clas

    javax.swing.JComboBox clas

### id

    javax.swing.JComboBox id

### colorList

    weka.core.FastVector colorList

### minC

    double minC

### maxC

    double maxC

### classIndex

    int classIndex

### idIndex

    int idIndex

### change

    java.beans.PropertyChangeSupport change

### m_DefaultColors

    java.awt.Color[] m_DefaultColors

Class milk.visualize.MIPlot2D implements Serializable

Serialized Fields

### plotExemplars

    Exemplars plotExemplars

  The instances to be plotted

### x

    Axis x

  The x and y axis, max and min values are of all the exemplars

### y

    Axis y

  The x and y axis, max and min values are of all the exemplars

### maxC

    double maxC

  Tempory variable to store maxC and minC in case the super.determineBounds() finds wrong ones.

### minC

    double minC

  Tempory variable to store maxC and minC in case the super.determineBounds() finds wrong ones.

Class milk.visualize.PlotPanel implements Serializable

Serialized Fields

### m_axisColour

    java.awt.Color m_axisColour

  Default colour for the axis

### m_backgroundColour

    java.awt.Color m_backgroundColour

  Default colour for the plot background

### plotExemplars

    Exemplars plotExemplars

  The exemplars to be plotted

### colorList

    weka.core.FastVector colorList

  The list of the colors used

### m_minC

    double m_minC

  The max and min color

### m_maxC

    double m_maxC

  The max and min color

### x

    Axis x

  Indexes of the attributes to go on the x axis

### stdDev

    double stdDev

  The std. deviations used in deriving the distributions

### maxY

    double maxY

  The maximal value in Y axis

### m_axisPad

    int m_axisPad

  Axis padding

  See Also:
    Constant Field Values

### m_tickSize

    int m_tickSize

  Tick size

  See Also:
    Constant Field Values

### m_XaxisStart

    int m_XaxisStart

  The offsets of the axes once label metrics are calculated

### m_XaxisEnd

    int m_XaxisEnd

### m_YaxisStart

    int m_YaxisStart

### m_YaxisEnd

    int m_YaxisEnd

### isUp

    boolean isUp

  Whether the distribution curve is up or down

### m_labelFont

    java.awt.Font m_labelFont

  Font for labels

### m_labelMetrics

    java.awt.FontMetrics m_labelMetrics

Class milk.visualize.SelectPanel implements Serializable

Serialized Fields

### choose

    javax.swing.JList choose

### added

    javax.swing.JList added

### chooseModel

    javax.swing.DefaultListModel chooseModel

### addModel

    javax.swing.DefaultListModel addModel

### add

    javax.swing.JButton add

### rm

    javax.swing.JButton rm

### addAll

    javax.swing.JButton addAll

### rmAll

    javax.swing.JButton rmAll

### jp

    javax.swing.JPanel jp

### exemplars

    Exemplars exemplars

### addedExs

    Exemplars addedExs

### pcs

    java.beans.PropertyChangeSupport pcs

### colorList

    weka.core.FastVector colorList

### m_minC

    double m_minC

### m_maxC

    double m_maxC

### chooseSP

    javax.swing.JScrollPane chooseSP

### addSP

    javax.swing.JScrollPane addSP