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U

uminus(). Method in class weka.classifiers.functions.pace.Matrix

Unary minus

UnassignedClassException exception weka.core.UnassignedClassException.

Exception that is raised when trying to use some data that has no class assigned to it, but a class is needed to perform the operation.

UnassignedClassException(). Constructor for class weka.core.UnassignedClassException

Creates a new UnassignedClassException with no message.

UnassignedClassException(String). Constructor for class weka.core.UnassignedClassException

Creates a new UnassignedClassException.

UnassignedDatasetException exception weka.core.UnassignedDatasetException.

Exception that is raised when trying to use something that has no reference to a dataset, when one is required.

UnassignedDatasetException(). Constructor for class weka.core.UnassignedDatasetException

Creates a new UnassignedDatasetException with no message.

UnassignedDatasetException(String). Constructor for class weka.core.UnassignedDatasetException

Creates a new UnassignedDatasetException.

unclassified(). Method in class weka.classifiers.Evaluation

Gets the number of instances not classified (that is, for which no prediction was made by the classifier).

UNCONNECTED. Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is not connected to any others.

undefinedDistribution. Static variable in class weka.classifiers.functions.pace.Maths

Distribution type: undefined

undo(). Method in class weka.gui.explorer.PreprocessPanel

Reverts to the last backed up version of the dataset.

unique(). Method in class weka.classifiers.functions.pace.DiscreteFunction

Makes each individual point value unique

uniqueCount. Variable in class weka.core.AttributeStats

The number of values that only appear once

unpivoting(IntVector, int). Method in class weka.classifiers.functions.pace.DoubleVector

Returns a vector from the pivoting indices.

unsorted(). Method in class weka.classifiers.functions.pace.DoubleVector

Returns true if vector not sorted

UnsupervisedAttributeEvaluator class weka.attributeSelection.UnsupervisedAttributeEvaluator.

Abstract unsupervised attribute evaluator.

UnsupervisedAttributeEvaluator(). Constructor for class weka.attributeSelection.UnsupervisedAttributeEvaluator

UnsupervisedFilter interface weka.filters.UnsupervisedFilter.

Interface for filters that do not need a class attribute.

UnsupervisedSubsetEvaluator class weka.attributeSelection.UnsupervisedSubsetEvaluator.

Abstract unsupervised attribute subset evaluator.

UnsupervisedSubsetEvaluator(). Constructor for class weka.attributeSelection.UnsupervisedSubsetEvaluator

UnsupportedAttributeTypeException exception weka.core.UnsupportedAttributeTypeException.

Exception that is raised by an object that is unable to process some of the attribute types it has been passed.

UnsupportedAttributeTypeException(). Constructor for class weka.core.UnsupportedAttributeTypeException

Creates a new UnsupportedAttributeTypeException with no message.

UnsupportedAttributeTypeException(String). Constructor for class weka.core.UnsupportedAttributeTypeException

Creates a new UnsupportedAttributeTypeException.

UnsupportedClassTypeException exception weka.core.UnsupportedClassTypeException.

Exception that is raised by an object that is unable to process the class type of the data it has been passed.

UnsupportedClassTypeException(). Constructor for class weka.core.UnsupportedClassTypeException

Creates a new UnsupportedClassTypeException with no message.

UnsupportedClassTypeException(String). Constructor for class weka.core.UnsupportedClassTypeException

Creates a new UnsupportedClassTypeException.

update(double). Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat

UpdateableClassifier interface weka.classifiers.UpdateableClassifier.

Interface to incremental classification models that can learn using one instance at a time.

updateChildPropertySheet(). Method in class weka.gui.GenericObjectEditor.GOEPanel

Updates the child property sheet, and creates if needed

updateClassifier(Instance). Method in interface weka.classifiers.UpdateableClassifier

Updates a classifier using the given instance.

updateClassifier(Instance). Method in class weka.classifiers.lazy.IBk

Adds the supplied instance to the training set

updateClassifier(Instance). Method in class weka.classifiers.lazy.LWL

Adds the supplied instance to the training set

updateClassifier(Instance). Method in class weka.classifiers.lazy.IB1

Updates the classifier.

updateClassifier(Instance). Method in class weka.classifiers.lazy.kstar.KStar

Adds the supplied instance to the training set

updateClassifier(Instance). Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

Updates the classifier.

updateClassifier(Instance). Method in class weka.classifiers.misc.HyperPipes

Updates the classifier.

updateClassifier(Instance). Method in class weka.classifiers.bayes.BayesNet

Updates the classifier with the given instance.

updateClassifier(Instance). Method in class weka.classifiers.bayes.NaiveBayes

Updates the classifier with the given instance.

updateClassifier(Instance). Method in class weka.classifiers.rules.Nnge

Updates the classifier using the given instance.

updateClassifier(Instance). Method in class weka.classifiers.functions.Winnow

Updates the classifier with a new learning example

upDateCounter(Instance). Method in class weka.associations.ItemSet

Updates counter of item set with respect to given transaction.

upDateCounters(FastVector, Instances). Static method in class weka.associations.ItemSet

Updates counters for a set of item sets and a set of instances.

updateKDTree(Instance). Method in class weka.core.KDTree

Adds one instance to the KDTree.

updatePriors(Instance). Method in class weka.classifiers.Evaluation

Updates the class prior probabilities (when incrementally training)

updateRanges(Instance). Method in class weka.core.DistanceFunction

Update the ranges if a new instance comes.

updateRanges(Instance, double[][]). Static method in class weka.core.Instances

Updates the ranges given a new instance.

updateRanges(Instance, int, double[][]). Static method in class weka.clusterers.XMeans

Function should be in the Instances class!! Updates the minimum and maximum and width values for all the attributes based on a new instance.

updateRangesFirst(Instance, int, double[][]). Method in class weka.core.Instances

Used to initialize the ranges.

updateRangesFirst(Instance, int, double[][]). Static method in class weka.clusterers.XMeans

Function should be in the Instances class!! Used to initialize the ranges.

updateResult(String). Method in class weka.gui.ResultHistoryPanel

Tells any component currently displaying the named result that the contents of the result text in the StringBuffer have been updated.

updateWeights(double, double). Method in class weka.classifiers.functions.neural.NeuralConnection

Call this function to update the weight values at this unit.

updateWeights(double, double). Method in class weka.classifiers.functions.neural.NeuralNode

Call this function to update the weight values at this unit.

updateWeights(NeuralNode, double, double). Method in class weka.classifiers.functions.neural.LinearUnit

This function will calculate what the change in weights should be and also update them.

updateWeights(NeuralNode, double, double). Method in interface weka.classifiers.functions.neural.NeuralMethod

This function will calculate what the change in weights should be and also update them.

updateWeights(NeuralNode, double, double). Method in class weka.classifiers.functions.neural.SigmoidUnit

This function will calculate what the change in weights should be and also update them.

upperBoundMinSupportTipText(). Method in class weka.associations.Apriori

Returns the tip text for this property

upperNumericBoundIsOpen(). Method in class weka.core.Attribute

Returns whether the upper numeric bound of the attribute is open.

upperSizeTipText(). Method in class weka.experiment.LearningRateResultProducer

Returns the tip text for this property

useADTreeTipText(). Method in class weka.classifiers.bayes.BayesNet

useBetterEncodingTipText(). Method in class weka.filters.supervised.attribute.Discretize

Returns the tip text for this property

useDefaultVisual(). Method in class weka.gui.beans.AbstractDataSource

Use the default images for a data source

useDefaultVisual(). Method in interface weka.gui.beans.Visible

Use the default visual representation

useDefaultVisual(). Method in class weka.gui.beans.DataVisualizer

Use the default appearance for this bean

useDefaultVisual(). Method in class weka.gui.beans.AbstractTestSetProducer

Use the default visual for this bean

useDefaultVisual(). Method in class weka.gui.beans.AbstractEvaluator

Use the default images for an evaluator

useDefaultVisual(). Method in class weka.gui.beans.Filter

Use the default visual appearance

useDefaultVisual(). Method in class weka.gui.beans.AbstractTrainingSetProducer

Use the default visual for this bean

useDefaultVisual(). Method in class weka.gui.beans.Classifier

Use the default visual appearance for this bean

useDefaultVisual(). Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Use the default visual for this bean

useDefaultVisual(). Method in class weka.gui.beans.TextViewer

Use the default visual appearance for this bean

useDefaultVisual(). Method in class weka.gui.beans.StripChart

Use the default visual appearance for this bean

useDefaultVisual(). Method in class weka.gui.beans.GraphViewer

Use the default visual appearance

useDefaultVisual(). Method in class weka.gui.beans.ClassAssigner

useDefaultVisual(). Method in class weka.gui.beans.AttributeSummarizer

Use the default appearance for this bean

useEqualFrequencyTipText(). Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Returns the tip text for this property

useFilter(Instances, Filter). Static method in class weka.filters.Filter

Filters an entire set of instances through a filter and returns the new set.

useKononenkoTipText(). Method in class weka.filters.supervised.attribute.Discretize

Returns the tip text for this property

useMissingTipText(). Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

UserClassifier class weka.classifiers.trees.UserClassifier.

Class for generating an user defined decision tree.

UserClassifier(). Constructor for class weka.classifiers.trees.UserClassifier

Constructor

userCommand(TreeDisplayEvent). Method in interface weka.gui.treevisualizer.TreeDisplayListener

Gets called when the user selects something, in the tree display.

userCommand(TreeDisplayEvent). Method in class weka.classifiers.trees.UserClassifier

Receives user choices from the tree view, and then deals with these choices.

userDataEvent(VisualizePanelEvent). Method in interface weka.gui.visualize.VisualizePanelListener

This method receives an object containing the shapes, instances inside and outside these shapes and the attributes these shapes were created in.

userDataEvent(VisualizePanelEvent). Method in class weka.classifiers.trees.UserClassifier

This receives shapes from the data view.

useResamplingTipText(). Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

UserRequestAcceptor interface weka.gui.beans.UserRequestAcceptor.

Interface to something that can accept requests from a user to perform some action

useTrainingTipText(). Method in class weka.attributeSelection.ClassifierSubsetEval

Returns the tip text for this property

Utils class weka.core.Utils.

Class implementing some simple utility methods.

Utils(). Constructor for class weka.core.Utils

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