All Packages  Class Hierarchy

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

E

Edge class weka.gui.treevisualizer.Edge.
This class is used in conjunction with the Node class to form a tree structure.
Edge(String, String, String). Constructor for class weka.gui.treevisualizer.Edge
This constructs an Edge with the specified label and parent , child serial tags.
editableProperties(). Method in class weka.gui.PropertySheetPanel
Gets the number of editable properties for the current target.
elementAt(int). Method in class weka.core.FastVector
Returns the element at the given position.
elements(). Method in class weka.core.FastVector
Returns an enumeration of this vector.
elements(int). Method in class weka.core.FastVector
Returns an enumeration of this vector, skipping the element with the given index.
EM class weka.clusterers.EM.
Simple EM (estimation maximisation) class.
EM(). Constructor for class weka.clusterers.EM
Constructor.
empty(). Method in class weka.core.Queue
Checks if queue is empty.
EmptyAttributeFilter class weka.filters.EmptyAttributeFilter.
Removes all attributes that do not contain more than one distinct value.
EmptyAttributeFilter(). Constructor for class weka.filters.EmptyAttributeFilter
entropy(double[]). Static method in class weka.core.ContingencyTables
Computes the entropy of the given array.
EntropyBasedSplitCrit class weka.classifiers.j48.EntropyBasedSplitCrit.
"Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropyBasedSplitCrit(). Constructor for class weka.classifiers.j48.EntropyBasedSplitCrit
entropyConditionedOnColumns(double[][]). Static method in class weka.core.ContingencyTables
Computes conditional entropy of the rows given the columns.
entropyConditionedOnRows(double[][]). Static method in class weka.core.ContingencyTables
Computes conditional entropy of the columns given the rows.
entropyConditionedOnRows(double[][], double[][], double). Static method in class weka.core.ContingencyTables
Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
entropyOverColumns(double[][]). Static method in class weka.core.ContingencyTables
Computes the columns' entropy for the given contingency table.
entropyOverRows(double[][]). Static method in class weka.core.ContingencyTables
Computes the rows' entropy for the given contingency table.
EntropySplitCrit class weka.classifiers.j48.EntropySplitCrit.
Class for computing the entropy for a given distribution.
EntropySplitCrit(). Constructor for class weka.classifiers.j48.EntropySplitCrit
enumerateAttributes(). Method in class weka.core.Instances
Returns an enumeration of all the attributes.
enumerateAttributes(). Method in class weka.core.Instance
Returns an enumeration of all the attributes.
enumerateInstances(). Method in class weka.core.Instances
Returns an enumeration of all instances in the dataset.
enumerateMeasures(). Method in class weka.classifiers.DecisionTable
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in class weka.classifiers.AttributeSelectedClassifier
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in class weka.classifiers.AdditiveRegression
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in class weka.classifiers.adtree.ADTree
Returns an enumeration of the additional measure names.
enumerateMeasures(). Method in class weka.classifiers.j48.J48
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in class weka.classifiers.j48.PART
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in class weka.classifiers.m5.M5Prime
Returns an enumeration of the additional measure names
enumerateMeasures(). Method in interface weka.core.AdditionalMeasureProducer
Returns an enumeration of the measure names.
enumerateMeasures(). Method in class weka.experiment.ClassifierSplitEvaluator
Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures(). Method in class weka.experiment.LearningRateResultProducer
Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures(). Method in class weka.experiment.CrossValidationResultProducer
Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures(). Method in class weka.experiment.RegressionSplitEvaluator
Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures(). Method in class weka.experiment.RandomSplitResultProducer
Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures(). Method in class weka.experiment.AveragingResultProducer
Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures(). Method in class weka.experiment.DatabaseResultProducer
Returns an enumeration of any additional measure names that might be in the result producer
enumerateValues(). Method in class weka.core.Attribute
Returns an enumeration of all the attribute's values if the attribute is nominal or a string, null otherwise.
EPSILON. Static variable in interface weka.classifiers.kstar.KStarConstants
eq(double, double). Static method in class weka.core.Utils
Tests if a is equal to b.
eqDouble(double, double). Static method in class weka.classifiers.m5.M5Utils
Tests if two double values are equal to each other
equalHeaders(Instance). Method in class weka.core.Instance
Tests if the headers of two instances are equivalent.
equalHeaders(Instances). Method in class weka.core.Instances
Checks if two headers are equivalent.
equals(Object). Method in class weka.associations.ItemSet
Tests if two item sets are equal.
equals(Object). Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
Tests if two instances are equal
equals(Object). Method in class weka.classifiers.DecisionTable.hashKey
Tests if two instances are equal
equals(Object). Method in class weka.classifiers.Evaluation
Tests whether the current evaluation object is equal to another evaluation object
equals(Object). Method in class weka.core.Attribute
Tests if given attribute is equal to this attribute.
equals(Object). Method in class weka.core.SelectedTag
Returns true if this SelectedTag equals another object
equals(Object). Method in class weka.core.SerializedObject
Compares this object with another for equality.
equalTo(Splitter). Method in class weka.classifiers.adtree.Splitter
Tests whether two splitters are equivalent.
equalTo(Splitter). Method in class weka.classifiers.adtree.TwoWayNominalSplit
Tests whether two splitters are equivalent.
equalTo(Splitter). Method in class weka.classifiers.adtree.TwoWayNumericSplit
Tests whether two splitters are equivalent.
errms(StreamTokenizer, String). Static method in class weka.core.converters.ConverterUtils
Throws error message with line number and last token read.
ERROR_EXHAUSTIVE. Static variable in class weka.classifiers.MultiClassClassifier
ERROR_NONE. Static variable in class weka.classifiers.MultiClassClassifier
The error correction modes
ERROR_RANDOM. Static variable in class weka.classifiers.MultiClassClassifier
ERROR_SHAPE. Static variable in class weka.gui.visualize.Plot2D
error(). Method in class weka.classifiers.evaluation.NumericPrediction
Calculates the prediction error.
ErrorBasedMeritEvaluator interface weka.attributeSelection.ErrorBasedMeritEvaluator.
Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
errorCorrectionModeTipText(). Method in class weka.classifiers.MultiClassClassifier
errorMsg(String). Static method in class weka.classifiers.m5.M5Utils
Prints error message and exits
errorRate(). Method in class weka.classifiers.Evaluation
Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorRate(). Method in class weka.classifiers.evaluation.ConfusionMatrix
Returns the estimated error rate.
Errors class weka.classifiers.m5.Errors.
Class for containing the evaluation results of a model
errors(Instances). Method in class weka.classifiers.m5.Function
Evaluates a function
errors(Instances, boolean). Method in class weka.classifiers.m5.Node
Evaluates a tree
Errors(int, int). Constructor for class weka.classifiers.m5.Errors
Constructs an object which could contain the evaluation results of a model
errorValue(boolean). Method in class weka.classifiers.neural.NeuralConnection
Call this to get the error value of this unit.
errorValue(boolean). Method in class weka.classifiers.neural.NeuralNode
Call this to get the error value of this unit.
errorValue(NeuralNode). Method in class weka.classifiers.neural.LinearUnit
This function calculates what the error value should be.
errorValue(NeuralNode). Method in class weka.classifiers.neural.SigmoidUnit
This function calculates what the error value should be.
errorValue(NeuralNode). Method in interface weka.classifiers.neural.NeuralMethod
This function calculates what the error value should be.
Estimator interface weka.estimators.Estimator.
Interface for probability estimators.
EVAL_CROSS_VALIDATION. Static variable in class weka.classifiers.ThresholdSelector
EVAL_TRAINING_SET. Static variable in class weka.classifiers.ThresholdSelector
EVAL_TUNED_SPLIT. Static variable in class weka.classifiers.ThresholdSelector
evaluateAttribute(int). Method in class weka.attributeSelection.AttributeEvaluator
evaluates an individual attribute
evaluateAttribute(int). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
evaluates an individual attribute by measuring the symmetrical uncertainty between it and the class.
evaluateAttribute(int). Method in class weka.attributeSelection.GainRatioAttributeEval
evaluates an individual attribute by measuring the gain ratio of the class given the attribute.
evaluateAttribute(int). Method in class weka.attributeSelection.ReliefFAttributeEval
Evaluates an individual attribute using ReliefF's instance based approach.
evaluateAttribute(int). Method in class weka.attributeSelection.ChiSquaredAttributeEval
evaluates an individual attribute by measuring its chi-squared value.
evaluateAttribute(int). Method in class weka.attributeSelection.OneRAttributeEval
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int). Method in class weka.attributeSelection.InfoGainAttributeEval
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int). Method in class weka.attributeSelection.PrincipalComponents
Evaluates the merit of a transformed attribute.
evaluateClusterer(Clusterer, String[]). Static method in class weka.clusterers.ClusterEvaluation
Evaluates a clusterer with the options given in an array of strings.
evaluateClusterer(Instances). Method in class weka.clusterers.ClusterEvaluation
Evaluate the clusterer on a set of instances.
evaluateModel(Classifier, Instances). Method in class weka.classifiers.Evaluation
Evaluates the classifier on a given set of instances.
evaluateModel(Classifier, String[]). Static method in class weka.classifiers.Evaluation
Evaluates a classifier with the options given in an array of strings.
evaluateModel(String, String[]). Static method in class weka.classifiers.Evaluation
Evaluates a classifier with the options given in an array of strings.
evaluateModelOnce(Classifier, Instance). Method in class weka.classifiers.Evaluation
Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance). Method in class weka.classifiers.Evaluation
Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance). Method in class weka.classifiers.Evaluation
Evaluates the supplied prediction on a single instance.
evaluateSubset(BitSet). Method in class weka.attributeSelection.SubsetEvaluator
evaluates a subset of attributes
evaluateSubset(BitSet). Method in class weka.attributeSelection.CfsSubsetEval
evaluates a subset of attributes
evaluateSubset(BitSet). Method in class weka.attributeSelection.ConsistencySubsetEval
Evaluates a subset of attributes
evaluateSubset(BitSet). Method in class weka.attributeSelection.ClassifierSubsetEval
Evaluates a subset of attributes
evaluateSubset(BitSet). Method in class weka.attributeSelection.WrapperSubsetEval
Evaluates a subset of attributes
evaluateSubset(BitSet, Instance, boolean). Method in class weka.attributeSelection.HoldOutSubsetEvaluator
Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet, Instance, boolean). Method in class weka.attributeSelection.ClassifierSubsetEval
Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet, Instances). Method in class weka.attributeSelection.HoldOutSubsetEvaluator
Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instances). Method in class weka.attributeSelection.ClassifierSubsetEval
Evaluates a subset of attributes with respect to a set of instances.
Evaluation class weka.classifiers.Evaluation.
Class for evaluating machine learning models.
Evaluation(Instances). Constructor for class weka.classifiers.Evaluation
Initializes all the counters for the evaluation.
Evaluation(Instances, CostMatrix). Constructor for class weka.classifiers.Evaluation
Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
evaluationModeTipText(). Method in class weka.classifiers.ThresholdSelector
EvaluationUtils class weka.classifiers.evaluation.EvaluationUtils.
Contains utility functions for generating lists of predictions in various manners.
EvaluationUtils(). Constructor for class weka.classifiers.evaluation.EvaluationUtils
evaluatorTipText(). Method in class weka.classifiers.AttributeSelectedClassifier
Returns the tip text for this property
execute(). Method in interface weka.experiment.Task
Execute this task.
execute(). Method in class weka.experiment.RemoteExperimentSubTask
Run the experiment
execute(String). Method in class weka.experiment.DatabaseUtils
Executes a SQL query.
executeTask(Task). Method in class weka.experiment.RemoteEngine
Takes a task object and queues it for execution
executeTask(Task). Method in interface weka.experiment.Compute
Execute a task
ExhaustiveSearch class weka.attributeSelection.ExhaustiveSearch.
Class for performing an exhaustive search.
ExhaustiveSearch(). Constructor for class weka.attributeSelection.ExhaustiveSearch
Constructor
EXP_INDEX_TABLE. Static variable in class weka.experiment.DatabaseUtils
The name of the table containing the index to experiments
EXP_RESULT_COL. Static variable in class weka.experiment.DatabaseUtils
The name of the column containing the results table name
EXP_RESULT_PREFIX. Static variable in class weka.experiment.DatabaseUtils
The prefix for result table names
EXP_SETUP_COL. Static variable in class weka.experiment.DatabaseUtils
The name of the column containing the experiment setup (parameters)
EXP_TYPE_COL. Static variable in class weka.experiment.DatabaseUtils
The name of the column containing the experiment type (ResultProducer)
expectedCosts(double[]). Method in class weka.classifiers.CostMatrix
Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedResultsPerAverageTipText(). Method in class weka.experiment.AveragingResultProducer
Returns the tip text for this property
Experiment class weka.experiment.Experiment.
Holds all the necessary configuration information for a standard type experiment.
Experiment(). Constructor for class weka.experiment.Experiment
Experimenter class weka.gui.experiment.Experimenter.
The main class for the experiment environment.
Experimenter(boolean). Constructor for class weka.gui.experiment.Experimenter
Creates the experiment environment gui with no initial experiment
experimentIndexExists(). Method in class weka.experiment.DatabaseUtils
Returns true if the experiment index exists.
Explorer class weka.gui.explorer.Explorer.
The main class for the Weka explorer.
Explorer(). Constructor for class weka.gui.explorer.Explorer
Creates the experiment environment gui with no initial experiment
expressionTipText(). Method in class weka.filters.AttributeExpressionFilter
Returns the tip text for this property
ExtensionFileFilter class weka.gui.ExtensionFileFilter.
Provides a file filter for FileChoosers that accepts or rejects files based on their extension.
ExtensionFileFilter(String, String). Constructor for class weka.gui.ExtensionFileFilter
Creates the ExtensionFileFilter

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Packages  Class Hierarchy