Uses of Class
meka.core.Result

Packages that use Result

Package	Description
meka.classifiers.multilabel
meka.classifiers.multilabel.incremental
meka.classifiers.multitarget
meka.core
meka.experiment.evaluationstatistics
meka.gui.core
meka.gui.explorer

Uses of Result in meka.classifiers.multilabel

Methods in meka.classifiers.multilabel that return Result

Modifier and Type	Method and Description
static Result	Evaluation.cvModel(MultiLabelClassifier h, weka.core.Instances D, int numFolds, String top) CVModel - Split D into train/test folds, and then train and evaluate on each one.
static Result	Evaluation.cvModel(MultiLabelClassifier h, weka.core.Instances D, int numFolds, String top, String vop) CVModel - Split D into train/test folds, and then train and evaluate on each one.
static Result	Evaluation.evaluateModel(MultiLabelClassifier h, weka.core.Instances D_train, weka.core.Instances D_test) EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test'.
static Result	Evaluation.evaluateModel(MultiLabelClassifier h, weka.core.Instances D_train, weka.core.Instances D_test, String top) EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test', threshold it according to 'top', using default verbosity option.
static Result	Evaluation.evaluateModel(MultiLabelClassifier h, weka.core.Instances D_train, weka.core.Instances D_test, String top, String vop) EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test', threshold it according to 'top', verbosity 'vop'.
static Result	Evaluation.evaluateModel(MultiLabelClassifier h, weka.core.Instances D_test, String tal, String vop) EvaluateModel - Assume 'h' is already built, test it on 'D_test', threshold it according to 'top', verbosity 'vop'.
static Result	Evaluation.evaluateModelM(MultiLabelClassifier h, weka.core.Instances D_train, weka.core.Instances D_test, String top, String vop)
static Result	Evaluation.testClassifier(MultiLabelClassifier h, weka.core.Instances D_test) TestClassifier - test classifier h on D_test
static Result	Evaluation.testClassifierM(MultiLabelClassifier h, weka.core.Instances D_test) Test Classifier but threaded (Multiple)

Uses of Result in meka.classifiers.multilabel.incremental

Methods in meka.classifiers.multilabel.incremental that return Result

Modifier and Type	Method and Description
static Result	IncrementalEvaluation.evaluateModel(MultiLabelClassifier h, weka.core.Instances D) EvaluateModel - over 20 windows.
static Result	IncrementalEvaluation.evaluateModel(MultiLabelClassifier h, String[] options) EvaluateModel - Build and evaluate.
static Result	IncrementalEvaluation.evaluateModelBatchWindow(MultiLabelClassifier h, weka.core.Instances D, int numWindows, double rLabeled, String Top, String Vop) EvaluateModelBatchWindow - Evaluate a multi-label data-stream model over windows.
static Result	IncrementalEvaluation.evaluateModelPrequentialBasic(MultiLabelClassifier h, weka.core.Instances D, int windowSize, double rLabeled, String Top, String Vop) Prequential Evaluation - Accuracy since the start of evaluation.

Uses of Result in meka.classifiers.multitarget

Methods in meka.classifiers.multitarget that return Result

Modifier and Type	Method and Description
Result	SCC.testClassifier(weka.classifiers.Classifier h, weka.core.Instances D_train, weka.core.Instances D_test, int[][] partition) Test classifier h, on dataset D, under super-class partition 'partition'.

Uses of Result in meka.core

Methods in meka.core that return Result

Modifier and Type	Method and Description
static Result	MLEvalUtils.averageResults(Result[] folds) Deprecated.
static Result	MLEvalUtils.combinePredictions(Result[] folds) Combine Predictions - Combine together various results (for example, from cross-validation) into one, simply by appending predictions and true values together, and averaging together their 'vals'.

Methods in meka.core with parameters of type Result

Modifier and Type	Method and Description
static Result	MLEvalUtils.averageResults(Result[] folds) Deprecated.
static Result	MLEvalUtils.combinePredictions(Result[] folds) Combine Predictions - Combine together various results (for example, from cross-validation) into one, simply by appending predictions and true values together, and averaging together their 'vals'.
static double[][]	StatUtils.condDepMatrix(weka.core.Instances D, Result result) CondDepMatrix - Get a Conditional Dependency Matrix.
static weka.core.Instances	Result.getPredictionsAsInstances(Result result) Convert predictions into Instances (and true values).
static String	Result.getResultAsString(Result s) GetResultAsString - print out each prediction in a Result along with its true labelset.
static String	Result.getResultAsString(Result result, int adp) GetResultAsString - print out each prediction in a Result (to a certain number of decimal points) along with its true labelset.
static HashMap<String,Object>	Result.getStats(Result r, String vop) GetStats.
static double[][]	StatUtils.LEAD(weka.core.Instances D, Result result)
static double[][]	StatUtils.LEAD(weka.core.Instances D, Result R, String MDType) LEAD - Performs LEAD on dataset 'D', with corresponding gresult 'R', and dependency measurement type 'MDType'.
static double[][]	StatUtils.LEAD2(weka.core.Instances D, Result result) LEAD.
static void	Result.writeResultToFile(Result result, String fname) WriteResultToFile -- write a Result 'result' out in plain text format to file 'fname'.

Uses of Result in meka.experiment.evaluationstatistics

Constructors in meka.experiment.evaluationstatistics with parameters of type Result

Constructor and Description
EvaluationStatistics(MultiLabelClassifier classifier, weka.core.Instances dataset, Result result) Extracts the statistics from the Result object.
EvaluationStatistics(MultiLabelClassifier classifier, String relation, Result result) Extracts the statistics from the Result object.

Uses of Result in meka.gui.core

Fields in meka.gui.core with type parameters of type Result

Modifier and Type	Field and Description
protected Hashtable<Date,Result>	ResultHistory.m_Results for storing the results (timestamp / result).

Methods in meka.gui.core that return Result

Modifier and Type	Method and Description
Result	ResultHistory.get(int index) Returns the specified history item.
Result	ResultHistoryList.getResultAt(int index) Returns the result at the specified location.
Result	ResultHistoryList.ResultHistoryModel.getResultAt(int index) Returns the element at the specified location.
Result	ResultHistory.remove(int index) Removes the specified entry.
Result	ResultHistoryList.ResultHistoryModel.removeElementAt(int index) Removes the element at the specified location.

Methods in meka.gui.core with parameters of type Result

Modifier and Type	Method and Description
void	ResultHistory.add(Result result, Object payload, String suffix) Adds the item to the history.
void	ResultHistoryList.ResultHistoryModel.addElement(Result result, Object payload, String suffix) Adds the element to the history.
void	ResultHistoryList.addResult(Result result, Object payload, String suffix) Adds the element to the history.

Uses of Result in meka.gui.explorer

Methods in meka.gui.explorer with parameters of type Result

Modifier and Type	Method and Description
void	ClassifyTab.addResultToHistory(Result result, Object payload, String suffix) Adds the result to the history.