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
B
- B_ENTROPY.
Static variable in interface weka.classifiers.kstar.KStarConstants
-
- B_SPHERE.
Static variable in interface weka.classifiers.kstar.KStarConstants
- Blend setting modes
- backQuoteChars(String).
Static method in class weka.core.Utils
- Converts carriage returns and new lines in a string into \r and \n.
- Bagging class weka.classifiers.Bagging.
- Class for bagging a classifier.
- Bagging().
Constructor for class weka.classifiers.Bagging
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- BATCH_FINISHED.
Static variable in class weka.gui.streams.InstanceEvent
- Specifies that the batch of instances is finished
- batchFilterFile(Filter, String[]).
Static method in class weka.filters.Filter
- Method for testing filters ability to process multiple batches.
- batchFinished().
Method in class weka.filters.Filter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.SpreadSubsampleFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.AbstractTimeSeriesFilter
- Signifies that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.StringToNominalFilter
- Signifies that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.EmptyAttributeFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.NormalizationFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.SplitDatasetFilter
- Signify that this batch of input to the filter is
finished.
- batchFinished().
Method in class weka.filters.ResampleFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.NominalToBinaryFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.ReplaceMissingValuesFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.AttributeSelectionFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.RandomizeFilter
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.filters.DiscretizeFilter
- Signifies that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.gui.streams.InstanceSavePanel
-
- batchFinished().
Method in class weka.gui.streams.InstanceViewer
-
- batchFinished().
Method in class weka.gui.streams.InstanceJoiner
- Signify that this batch of input to the filter is finished.
- batchFinished().
Method in class weka.gui.streams.InstanceTable
-
- BestFirst class weka.attributeSelection.BestFirst.
- Class for performing a best first search.
- BestFirst.Link2 class weka.attributeSelection.BestFirst.Link2.
- Class for a node in a linked list.
- BestFirst.Link2(BestFirst, BitSet, double).
Constructor for class weka.attributeSelection.BestFirst.Link2
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- BestFirst.LinkedList2 class weka.attributeSelection.BestFirst.LinkedList2.
- Class for handling a linked list.
- BestFirst.LinkedList2(BestFirst, int).
Constructor for class weka.attributeSelection.BestFirst.LinkedList2
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- BestFirst().
Constructor for class weka.attributeSelection.BestFirst
- Constructor
- biasTipText().
Method in class weka.classifiers.VFI
- Returns the tip text for this property
- binarizeNumericAttributesTipText().
Method in class weka.attributeSelection.ChiSquaredAttributeEval
- Returns the tip text for this property
- binarizeNumericAttributesTipText().
Method in class weka.attributeSelection.InfoGainAttributeEval
- Returns the tip text for this property
- BinarySparseInstance class weka.core.BinarySparseInstance.
- Class for storing a binary-data-only instance as a sparse vector.
- BinarySparseInstance(double, double[]).
Constructor for class weka.core.BinarySparseInstance
- Constructor that generates a sparse instance from the given
parameters.
- BinarySparseInstance(double, int[], int).
Constructor for class weka.core.BinarySparseInstance
- Constructor that inititalizes instance variable with given
values.
- BinarySparseInstance(Instance).
Constructor for class weka.core.BinarySparseInstance
- Constructor that generates a sparse instance from the given
instance.
- BinarySparseInstance(int).
Constructor for class weka.core.BinarySparseInstance
- Constructor of an instance that sets weight to one, all values to
1, and the reference to the dataset to null.
- BinarySparseInstance(SparseInstance).
Constructor for class weka.core.BinarySparseInstance
- Constructor that copies the info from the given instance.
- BinC45ModelSelection class weka.classifiers.j48.BinC45ModelSelection.
- Class for selecting a C4.5-like binary (!) split for a given dataset.
- BinC45ModelSelection(int, Instances).
Constructor for class weka.classifiers.j48.BinC45ModelSelection
- Initializes the split selection method with the given parameters.
- BinC45Split class weka.classifiers.j48.BinC45Split.
- Class implementing a binary C4.5-like split on an attribute.
- BinC45Split(int, int, double).
Constructor for class weka.classifiers.j48.BinC45Split
- Initializes the split model.
- binomialStandardError(double, int).
Static method in class weka.core.Statistics
- Computes standard error for observed values of a binomial
random variable.
- binsTipText().
Method in class weka.filters.DiscretizeFilter
- Returns the tip text for this property
- blocker(boolean).
Method in class weka.classifiers.neural.NeuralNetwork
- A function used to stop the code that called buildclassifier
from continuing on before the user has finished the decision tree.
- boost().
Method in class weka.classifiers.adtree.ADTree
- Performs a single boosting iteration, using two-class optimized method.
- branchInstanceGoesDown(Instance).
Method in class weka.classifiers.adtree.Splitter
- Gets the index of the branch that an instance applies to.
- branchInstanceGoesDown(Instance).
Method in class weka.classifiers.adtree.TwoWayNominalSplit
- Gets the index of the branch that an instance applies to.
- branchInstanceGoesDown(Instance).
Method in class weka.classifiers.adtree.TwoWayNumericSplit
- Gets the index of the branch that an instance applies to.
- buildAssociations(Instances).
Method in class weka.associations.Associator
- Generates an associator.
- buildAssociations(Instances).
Method in class weka.associations.Apriori
- Method that generates all large itemsets with a minimum support, and from
these all association rules with a minimum confidence.
- buildClassifier(Instances).
Method in class weka.classifiers.Classifier
- Generates a classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.MetaCost
- Builds the model of the base learner.
- buildClassifier(Instances).
Method in class weka.classifiers.Prism
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.DecisionTable
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.DecisionStump
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.AdaBoostM1
- Boosting method.
- buildClassifier(Instances).
Method in class weka.classifiers.ClassificationViaRegression
- Builds the classifiers.
- buildClassifier(Instances).
Method in class weka.classifiers.AttributeSelectedClassifier
- Build the classifier on the dimensionally reduced data.
- buildClassifier(Instances).
Method in class weka.classifiers.Stacking
- Buildclassifier selects a classifier from the set of classifiers
by minimising error on the training data.
- buildClassifier(Instances).
Method in class weka.classifiers.CVParameterSelection
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.OneR
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.Bagging
- Bagging method.
- buildClassifier(Instances).
Method in class weka.classifiers.ThresholdSelector
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.KernelDensity
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.IBk
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.ZeroR
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.RegressionByDiscretization
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.IB1
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.LogitBoost
- Boosting method.
- buildClassifier(Instances).
Method in class weka.classifiers.HyperPipes
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.Id3
- Builds Id3 decision tree classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.MultiClassClassifier
- Builds the classifiers.
- buildClassifier(Instances).
Method in class weka.classifiers.MultiScheme
- Buildclassifier selects a classifier from the set of classifiers
by minimising error on the training data.
- buildClassifier(Instances).
Method in class weka.classifiers.UserClassifier
- Call this function to build a decision tree for the training
data provided.
- buildClassifier(Instances).
Method in class weka.classifiers.AdditiveRegression
- Build the classifier on the supplied data
- buildClassifier(Instances).
Method in class weka.classifiers.CostSensitiveClassifier
- Builds the model of the base learner.
- buildClassifier(Instances).
Method in class weka.classifiers.NaiveBayes
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.SMO
- Method for building the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.Logistic
- Builds the classifier
- buildClassifier(Instances).
Method in class weka.classifiers.LWR
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.VotedPerceptron
- Builds the ensemble of perceptrons.
- buildClassifier(Instances).
Method in class weka.classifiers.NaiveBayesSimple
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.DistributionMetaClassifier
- Builds the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.VFI
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.LinearRegression
- Builds a regression model for the given data.
- buildClassifier(Instances).
Method in class weka.classifiers.FilteredClassifier
- Build the classifier on the filtered data.
- buildClassifier(Instances).
Method in class weka.classifiers.adtree.ADTree
- Builds a classifier for a set of instances.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.ClassifierSplitModel
- Builds the classifier split model for the given set of instances.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.J48
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.ClassifierTree
- Method for building a classifier tree.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.NoSplit
- Creates a "no-split"-split for a given set of instances.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.BinC45Split
- Creates a C4.5-type split on the given data.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.MakeDecList
- Builds dec list.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.PruneableClassifierTree
- Method for building a pruneable classifier tree.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.PART
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.C45Split
- Creates a C4.5-type split on the given data.
- buildClassifier(Instances).
Method in class weka.classifiers.j48.C45PruneableClassifierTree
- Method for building a pruneable classifier tree.
- buildClassifier(Instances).
Method in class weka.classifiers.kstar.KStar
- Generates the classifier.
- buildClassifier(Instances).
Method in class weka.classifiers.m5.M5Prime
- Construct a model tree by training instances
- buildClassifier(Instances).
Method in class weka.classifiers.neural.NeuralNetwork
- Call this function to build and train a neural network for the training
data provided.
- buildClusterer(Instances).
Method in class weka.clusterers.Clusterer
- Generates a clusterer.
- buildClusterer(Instances).
Method in class weka.clusterers.Cobweb
- Builds the clusterer.
- buildClusterer(Instances).
Method in class weka.clusterers.SimpleKMeans
- Generates a clusterer.
- buildClusterer(Instances).
Method in class weka.clusterers.EM
- Generates a clusterer.
- buildClusterer(Instances).
Method in class weka.clusterers.DistributionMetaClusterer
- Builds the clusterer.
- buildDecList(Instances, boolean).
Method in class weka.classifiers.j48.ClassifierDecList
- Builds the partial tree without hold out set.
- buildDecList(Instances, Instances, boolean).
Method in class weka.classifiers.j48.ClassifierDecList
- Builds the partial tree with hold out set
- buildEvaluator(Instances).
Method in class weka.attributeSelection.ASEvaluation
- Generates a attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
- Initializes a symmetrical uncertainty attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.GainRatioAttributeEval
- Initializes a gain ratio attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.CfsSubsetEval
- Generates a attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.ReliefFAttributeEval
- Initializes a ReliefF attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.ChiSquaredAttributeEval
- Initializes a chi-squared attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.OneRAttributeEval
- Initializes an information gain attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.InfoGainAttributeEval
- Initializes an information gain attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.ConsistencySubsetEval
- Generates a attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.ClassifierSubsetEval
- Generates a attribute evaluator.
- buildEvaluator(Instances).
Method in class weka.attributeSelection.PrincipalComponents
- Initializes principal components and performs the analysis
- buildEvaluator(Instances).
Method in class weka.attributeSelection.WrapperSubsetEval
- Generates a attribute evaluator.
- buildRule(Instances).
Method in class weka.classifiers.j48.C45PruneableDecList
- Method for building a pruned partial tree.
- buildRule(Instances, Instances).
Method in class weka.classifiers.j48.PruneableDecList
- Method for building a pruned partial tree.
- buildTree(Instances, boolean).
Method in class weka.classifiers.j48.ClassifierTree
- Builds the tree structure.
- buildTree(Instances, Instances, boolean).
Method in class weka.classifiers.j48.ClassifierTree
- Builds the tree structure with hold out set
- BVDecompose class weka.classifiers.BVDecompose.
- Class for performing a Bias-Variance decomposition on any classifier
using the method specified in:
R.
- BVDecompose().
Constructor for class weka.classifiers.BVDecompose
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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