Implements the "Farthest First Traversal Algorithm" by
Hochbaum and Shmoys 1985: A best possible heuristic for the
k-center problem, Mathematics of Operations Research, 10(2):180-184,
as cited by Sanjoy Dasgupta "performance guarantees for hierarchical
clustering", colt 2002, sydney
works as a fast simple approximate clusterer
modelled after SimpleKMeans, might be a useful initializer for it
Valid options are:
-N
Specify the number of clusters to generate.FarthestFirst().
Constructor for class weka.clusterers.FarthestFirst
FastVector class weka.core.FastVector.Implements a fast vector class without synchronized
methods.FastVector.FastVectorEnumeration class weka.core.FastVector.FastVectorEnumeration.Class for enumerating the vector's elements.FastVector.FastVectorEnumeration(FastVector, FastVector).
Constructor for class weka.core.FastVector.FastVectorEnumeration
Constructs an enumeration.
FastVector.FastVectorEnumeration(FastVector, FastVector, int).
Constructor for class weka.core.FastVector.FastVectorEnumeration
Constructs an enumeration with a special element.
FastVector().
Constructor for class weka.core.FastVector
Constructs an empty vector with initial
capacity zero.
FastVector(int).
Constructor for class weka.core.FastVector
Constructs a vector with the given capacity.
FastVector(int, int, double).
Constructor for class weka.core.FastVector
Constructs a vector with the given capacity, capacity
increment and capacity mulitplier.
FILE_EXTENSION.
Static variable in class weka.core.Instances
The filename extension that should be used for arff files
FILE_EXTENSION.
Static variable in class weka.experiment.Experiment
The filename extension that should be used for experiment files
FILE_EXTENSION.
Static variable in class weka.classifiers.CostMatrix
The deafult file extension for cost matrix files
FileEditor class weka.gui.FileEditor.A PropertyEditor for File objects that lets the user select a file.FileEditor().
Constructor for class weka.gui.FileEditor
Filter class weka.gui.beans.Filter.A wrapper bean for Weka filtersFilter class weka.filters.Filter.An abstract class for instance filters: objects that take instances
as input, carry out some transformation on the instance and then
output the instance.FILTER_NONE.
Static variable in class weka.classifiers.functions.supportVector.SMO
FILTER_NONE.
Static variable in class weka.classifiers.functions.supportVector.SMOreg
FILTER_NORMALIZE.
Static variable in class weka.classifiers.functions.supportVector.SMO
The filter to apply to the training data
FILTER_NORMALIZE.
Static variable in class weka.classifiers.functions.supportVector.SMOreg
The filter to apply to the training data
FILTER_STANDARDIZE.
Static variable in class weka.classifiers.functions.supportVector.SMO
FILTER_STANDARDIZE.
Static variable in class weka.classifiers.functions.supportVector.SMOreg
Filter().
Constructor for class weka.gui.beans.Filter
Filter().
Constructor for class weka.filters.Filter
FilterBeanInfo class weka.gui.beans.FilterBeanInfo.Bean info class for the Filter beanFilterBeanInfo().
Constructor for class weka.gui.beans.FilterBeanInfo
FilterCustomizer class weka.gui.beans.FilterCustomizer.GUI customizer for the filter beanFilterCustomizer().
Constructor for class weka.gui.beans.FilterCustomizer
FilteredClassifier class weka.classifiers.meta.FilteredClassifier.Class for running an arbitrary classifier on data that has been passed
through an arbitrary filter.
Valid options from the command line are:
-B classifierstring
Classifierstring should contain the full class name of a classifier
followed by options to the classifier.
FilteredClassifier().
Constructor for class weka.classifiers.meta.FilteredClassifier
Default constructor specifying ZeroR as the classifier and
AllFilter as the filter.
FilteredClassifier(Classifier, Filter).
Constructor for class weka.classifiers.meta.FilteredClassifier
Constructor that specifies the subclassifier and filter to use.
filterFile(Filter, String[]).
Static method in class weka.filters.Filter
Method for testing filters.
filterTypeTipText().
Method in class weka.attributeSelection.SVMAttributeEval
Returns a tip text for this property suitable for display in the
GUI
findArgmin(double[], double[][]).
Method in class weka.core.Optimization
Main algorithm.
findBestLeaf(double[], RuleNode[]).
Method in class weka.classifiers.trees.m5.RuleNode
Find the leaf with greatest coverage
findInstance(Point).
Static method in class weka.gui.beans.BeanInstance
Looks for a bean (if any) whose bounds contain the supplied point
findKNearestNeighbour(Instance, int, int[], double[]).
Method in class weka.core.KDTree
Find k nearest neighbours to target.
findNumBinsTipText().
Method in class weka.filters.unsupervised.attribute.Discretize
Returns the tip text for this property
findNumBinsTipText().
Method in class weka.filters.unsupervised.attribute.PKIDiscretize
Returns the tip text for this property
FINISHED.
Static variable in class weka.experiment.TaskStatusInfo
finished().
Method in class weka.experiment.OutputZipper
Closes the zip file.
firstElement().
Method in class weka.core.FastVector
Returns the first element of the vector.
firstInstance().
Method in class weka.core.Instances
Returns the first instance in the set.
FirstOrder class weka.filters.unsupervised.attribute.FirstOrder.This instance filter takes a range of N numeric attributes and replaces
them with N-1 numeric attributes, the values of which are the difference
between consecutive attribute values from the original instance.FirstOrder().
Constructor for class weka.filters.unsupervised.attribute.FirstOrder
fit(DoubleVector).
Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fit(DoubleVector, int).
Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fitForSingleCluster(DoubleVector, int).
Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fittingIntervals(DoubleVector).
Method in class weka.classifiers.functions.pace.MixtureDistribution
Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector).
Method in class weka.classifiers.functions.pace.ChisqMixture
Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector).
Method in class weka.classifiers.functions.pace.NormalMixture
Contructs the set of fitting intervals for mixture estimation.
fitToScreen().
Method in class weka.gui.treevisualizer.TreeVisualizer
Fits the tree to the current screen size.
FlexibleDecimalFormat class weka.classifiers.functions.pace.FlexibleDecimalFormat.FlexibleDecimalFormat().
Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(double).
Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int).
Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean).
Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean, boolean, boolean).
Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FloatingPointFormat class weka.classifiers.functions.pace.FloatingPointFormat.Class for the format of floating point numbersFloatingPointFormat().
Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
Default constructor
FloatingPointFormat(int).
Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FloatingPointFormat(int, int).
Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FloatingPointFormat(int, int, boolean).
Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FLOOR.
Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FLOOR1.
Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FMEASURE_NAME.
Static variable in class weka.classifiers.evaluation.ThresholdCurve
fMeasure(int).
Method in class weka.classifiers.Evaluation
Calculate the F-Measure with respect to a particular class.
FOLD_FIELD_NAME.
Static variable in class weka.experiment.CrossValidationResultProducer
foldsTipText().
Method in class weka.gui.beans.CrossValidationFoldMaker
Tip text for this property
foldsTipText().
Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
foldsTipText().
Method in class weka.attributeSelection.WrapperSubsetEval
Returns the tip text for this property
foldTipText().
Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
Returns the tip text for this property
foldTipText().
Method in class weka.filters.unsupervised.instance.RemoveFolds
Returns the tip text for this property
FORMAT_AVAILABLE.
Static variable in class weka.gui.beans.InstanceEvent
FORMAT_AVAILABLE.
Static variable in class weka.gui.streams.InstanceEvent
Specifies that the instance format is available
format(double, StringBuffer, FieldPosition).
Method in class weka.classifiers.functions.pace.ExponentialFormat
format(double, StringBuffer, FieldPosition).
Method in class weka.classifiers.functions.pace.FloatingPointFormat
format(double, StringBuffer, FieldPosition).
Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
formatDate(double).
Method in class weka.core.Attribute
formatString(String).
Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
forName(Class, String, String[]).
Static method in class weka.core.Utils
Creates a new instance of an object given it's class name and
(optional) arguments to pass to it's setOptions method.
forName(String, String[]).
Static method in class weka.clusterers.Clusterer
Creates a new instance of a clusterer given it's class name and
(optional) arguments to pass to it's setOptions method.
forName(String, String[]).
Static method in class weka.attributeSelection.ASSearch
Creates a new instance of a search class given it's class name and
(optional) arguments to pass to it's setOptions method.
forName(String, String[]).
Static method in class weka.attributeSelection.ASEvaluation
Creates a new instance of an attribute/subset evaluator
given it's class name and
(optional) arguments to pass to it's setOptions method.
forName(String, String[]).
Static method in class weka.associations.Associator
Creates a new instance of a associator given it's class name and
(optional) arguments to pass to it's setOptions method.
forName(String, String[]).
Static method in class weka.classifiers.Classifier
Creates a new instance of a classifier given it's class name and
(optional) arguments to pass to it's setOptions method.
forward(PaceMatrix, IntVector, int).
Method in class weka.classifiers.functions.pace.PaceMatrix
Forward ordering of columns in terms of response explanation.
ForwardSelection class weka.attributeSelection.ForwardSelection.Class for performing a forward selection hill climbing search.ForwardSelection().
Constructor for class weka.attributeSelection.ForwardSelection
FP_RATE_NAME.
Static variable in class weka.classifiers.evaluation.ThresholdCurve
FProbability(double, int, int).
Static method in class weka.core.Statistics
Computes probability of F-ratio.
FREQ_ASCEND.
Static variable in class weka.filters.supervised.attribute.ClassOrder
The class values are sorted in ascending order based on their frequencies
FREQ_DESCEND.
Static variable in class weka.filters.supervised.attribute.ClassOrder
The class values are sorted in descending order based on their frequencies
fullValue().
Method in class weka.gui.HierarchyPropertyParser
The full value of the current node, i.e.