Class for evaluating clustering models.
Valid options are:
-t
Specify the training file.ClusterEvaluation().
Constructor for class weka.clusterers.ClusterEvaluation
Constructor.
clusterInstance(Instance).
Method in class weka.clusterers.Clusterer
Classifies a given instance.
clusterInstance(Instance).
Method in class weka.clusterers.DistributionClusterer
Assigns an instance to a Cluster.
clusterInstance(Instance).
Method in class weka.clusterers.FarthestFirst
Classifies a given instance.
clusterInstance(Instance).
Method in class weka.clusterers.SimpleKMeans
Classifies a given instance.
clusterInstance(Instance).
Method in class weka.clusterers.XMeans
Classifies a given instance.
clusterInstance(Instance).
Method in class weka.clusterers.Cobweb
Classifies a given instance.
clusterResultsToString().
Method in class weka.clusterers.ClusterEvaluation
return the results of clustering.
Cobweb class weka.clusterers.Cobweb.Class implementing the Cobweb and Classit clustering algorithms.
Note: the application of node operators (merging, splitting etc.) in
terms of ordering and priority differs (and is somewhat ambiguous)
between the original Cobweb and Classit papers.
Cobweb().
Constructor for class weka.clusterers.Cobweb
cochransCriterion(double[][]).
Static method in class weka.core.ContingencyTables
Tests if Cochran's criterion is fullfilled for the given
contingency table.
codingCost().
Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Returns coding costs of model.
codingCost().
Method in class weka.classifiers.trees.j48.C45Split
Returns coding cost for split (used in rule learner).
coefficients().
Method in class weka.classifiers.functions.LinearRegression
Returns the coefficients for this linear model.
coefficients().
Method in class weka.classifiers.functions.pace.PaceRegression
Returns the coefficients for this linear model.
collapse().
Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
Collapses a tree to a node if training error doesn't increase.
Colors class weka.gui.treevisualizer.Colors.This class maintains a list that contains all the colornames from the
dotty standard and what color (in RGB) they representColors().
Constructor for class weka.gui.treevisualizer.Colors
columnResponseExplanation(PaceMatrix, IntVector, int, int).
Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the squared ks-th response value if the j-th column becomes
the ks-th after orthogonal transformation.
combinations(int, int).
Static method in class weka.classifiers.functions.LeastMedSq
Produces the combination nCr
combinedDL(double, double).
Method in class weka.classifiers.rules.RuleStats
Compute the combined DL of the ruleset in this class, i.e.
compactify().
Method in class weka.core.Instances
Compactifies the set of instances.
compareOptions(String[], String[]).
Static method in class weka.core.CheckOptionHandler
Compares the two given sets of options.
comparisonString(int, Instances).
Method in class weka.classifiers.trees.adtree.Splitter
Gets the string describing the comparision the split depends on for a particular
branch.
comparisonString(int, Instances).
Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the string describing the comparision the split depends on for a particular
branch.
comparisonString(int, Instances).
Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the string describing the comparision the split depends on for a particular
branch.
complexityParameterTipText().
Method in class weka.attributeSelection.SVMAttributeEval
Returns a tip text for this property suitable for display in the
GUI
Compute interface weka.experiment.Compute.Interface to something that can accept remote connections and execute
a task.ConditionalEstimator interface weka.estimators.ConditionalEstimator.Interface for conditional probability estimators.confidenceForRule(ItemSet, ItemSet).
Static method in class weka.associations.ItemSet
Outputs the confidence for a rule.
ConfusionMatrix class weka.classifiers.evaluation.ConfusionMatrix.Cells of this matrix correspond to counts of the number (or weight)
of predictions for each actual value / predicted value combination.confusionMatrix().
Method in class weka.classifiers.Evaluation
Returns a copy of the confusion matrix.
ConfusionMatrix(String[]).
Constructor for class weka.classifiers.evaluation.ConfusionMatrix
Creates the confusion matrix with the given class names.
ConjunctiveRule class weka.classifiers.rules.ConjunctiveRule.This class implements a single conjunctive rule learner that can predict
for numeric and nominal class labels.
A rule consists of antecedents "AND"ed together and the consequent (class value)
for the classification/regression.
ConjunctiveRule().
Constructor for class weka.classifiers.rules.ConjunctiveRule
connect(NeuralConnection, NeuralConnection).
Static method in class weka.classifiers.functions.neural.NeuralConnection
Connects two units together.
CONNECTED.
Static variable in class weka.classifiers.functions.neural.NeuralConnection
This flag is set once the unit has a connection.
connectionAllowed(String).
Method in class weka.gui.beans.AbstractTestSetProducer
Returns true if, at this time,
the object will accept a connection according to the supplied
event name
connectionAllowed(String).
Method in class weka.gui.beans.AbstractEvaluator
Returns true if, at this time,
the object will accept a connection according to the supplied
event name
connectionAllowed(String).
Method in class weka.gui.beans.Filter
Returns true if, at this time,
the object will accept a connection with respect to the supplied
event name
connectionAllowed(String).
Method in class weka.gui.beans.AbstractTrainingSetProducer
Returns true if, at this time,
the object will accept a connection according to the supplied
event name
connectionAllowed(String).
Method in class weka.gui.beans.Classifier
Returns true if, at this time,
the object will accept a connection with respect to the named event
connectionAllowed(String).
Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Returns true if, at this time,
the object will accept a connection according to the supplied
event name
connectionAllowed(String).
Method in class weka.gui.beans.StripChart
Returns true if, at this time,
the object will accept a connection via the named event
connectionAllowed(String).
Method in class weka.gui.beans.ClassAssigner
Returns true if, at this time,
the object will accept a connection according to the supplied
event name
connectionAllowed(String).
Method in interface weka.gui.beans.BeanCommon
Returns true if, at this time,
the object will accept a connection via the named event
connectionNotification(String, Object).
Method in class weka.gui.beans.AbstractTestSetProducer
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in class weka.gui.beans.AbstractEvaluator
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in class weka.gui.beans.Filter
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in class weka.gui.beans.AbstractTrainingSetProducer
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in class weka.gui.beans.Classifier
Notify this object that it has been registered as a listener with
a source with respect to the named event
connectionNotification(String, Object).
Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in class weka.gui.beans.StripChart
Notify this object that it has been registered as a listener with
a source for recieving events described by the named event
This object is responsible for recording this fact.
connectionNotification(String, Object).
Method in class weka.gui.beans.ClassAssigner
Notify this object that it has been registered as a listener with
a source with respect to the supplied event name
connectionNotification(String, Object).
Method in interface weka.gui.beans.BeanCommon
Notify this object that it has been registered as a listener with
a source for recieving events described by the named event
This object is responsible for recording this fact.
CONNECTIONS.
Static variable in class weka.gui.beans.BeanConnection
The list of connections
connectToDatabase().
Method in class weka.experiment.DatabaseUtils
Opens a connection to the database
ConsistencySubsetEval class weka.attributeSelection.ConsistencySubsetEval.Consistency attribute subset evaluator.ConsistencySubsetEval.hashKey class weka.attributeSelection.ConsistencySubsetEval.hashKey.Class providing keys to the hash table.ConsistencySubsetEval.hashKey(ConsistencySubsetEval, double[]).
Constructor for class weka.attributeSelection.ConsistencySubsetEval.hashKey
Constructor for a hashKey
ConsistencySubsetEval.hashKey(ConsistencySubsetEval, Instance, int).
Constructor for class weka.attributeSelection.ConsistencySubsetEval.hashKey
Constructor for a hashKey
ConsistencySubsetEval().
Constructor for class weka.attributeSelection.ConsistencySubsetEval
Constructor.
CONST_AUTOMATIC_SHAPE.
Static variable in class weka.gui.visualize.Plot2D
constructWithCopy(double[][]).
Static method in class weka.classifiers.functions.pace.Matrix
Construct a matrix from a copy of a 2-D array.
containedBy(Instance).
Method in class weka.associations.ItemSet
Checks if an instance contains an item set.
contains(int).
Method in class weka.classifiers.functions.supportVector.SMOset
Checks whether an element is in the set.
contains(String).
Method in class weka.gui.HierarchyPropertyParser
Whether the HierarchyPropertyParser contains the given
string
containsKey(double).
Method in class weka.classifiers.lazy.kstar.KStarCache
Checks if the specified key maps with an entry in the cache table
containsKey(double).
Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
Tests if the specified double is a key in this hashtable.
context().
Method in class weka.gui.HierarchyPropertyParser
The context of the current node, i.e.
ContingencyTables class weka.core.ContingencyTables.Class implementing some statistical routines for contingency tables.ContingencyTables().
Constructor for class weka.core.ContingencyTables
ConverterUtils class weka.core.converters.ConverterUtils.Utility routines for the converter package.ConverterUtils().
Constructor for class weka.core.converters.ConverterUtils
convertInstance(Instance).
Method in interface weka.attributeSelection.AttributeTransformer
Transforms an instance in the format of the original data to the
transformed space
convertInstance(Instance).
Method in class weka.attributeSelection.PrincipalComponents
Transform an instance in original (unormalized) format.
convertNewLines(String).
Static method in class weka.core.Utils
Converts carriage returns and new lines in a string into \r and \n.
convertToAttribX(double).
Method in class weka.gui.visualize.Plot2D
convert a Panel x coordinate to a raw x value.
convertToAttribY(double).
Method in class weka.gui.visualize.Plot2D
convert a Panel y coordinate to a raw y value.
convertToPanelX(double).
Method in class weka.gui.visualize.Plot2D
Convert an raw x value to Panel x coordinate.
convertToPanelY(double).
Method in class weka.gui.visualize.Plot2D
Convert an raw y value to Panel y coordinate.
convictionForRule(ItemSet, ItemSet, int, int).
Method in class weka.associations.ItemSet
Outputs the conviction for a rule.
Copy class weka.filters.unsupervised.attribute.Copy.An instance filter that copies a range of attributes in the dataset.copy().
Method in class weka.core.Instance
Produces a shallow copy of this instance.
copy().
Method in class weka.core.SparseInstance
Produces a shallow copy of this instance.
copy().
Method in class weka.core.BinarySparseInstance
Produces a shallow copy of this instance.
copy().
Method in class weka.core.Attribute
Produces a shallow copy of this attribute.
copy().
Method in class weka.core.FastVector
Produces a shallow copy of this vector.
copy().
Method in interface weka.core.Copyable
This method produces a shallow copy of an object.
copy().
Method in class weka.classifiers.rules.Rule
Get a shallow copy of this rule
copy().
Method in interface weka.classifiers.trees.m5.SplitEvaluate
makes a copy of the SplitEvaluate object
copy().
Method in class weka.classifiers.trees.m5.YongSplitInfo
Makes a copy of this SplitInfo object
copy().
Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
Makes a copy of this CorrelationSplitInfo object
copy().
Method in class weka.classifiers.functions.pace.Matrix
Make a deep copy of a matrix
copy().
Method in class weka.classifiers.functions.pace.DoubleVector
Makes a deep copy of the vector
copy().
Method in class weka.classifiers.functions.pace.IntVector
Makes a deep copy of the vector
Copy().
Constructor for class weka.filters.unsupervised.attribute.Copy
Copyable interface weka.core.Copyable.Interface implemented by classes that can produce "shallow" copies
of their objects.copyElements().
Method in class weka.core.FastVector
Clones the vector and shallow copies all its elements.
correct().
Method in class weka.classifiers.Evaluation
Gets the number of instances correctly classified (that is, for
which a correct prediction was made).
correct().
Method in class weka.classifiers.evaluation.ConfusionMatrix
Gets the number of correct classifications (that is, for which a
correct prediction was made).
correlation.
Variable in class weka.experiment.PairedStats
The correlation coefficient
correlation(double[], double[], int).
Static method in class weka.core.Utils
Returns the correlation coefficient of two double vectors.
correlationCoefficient().
Method in class weka.classifiers.Evaluation
Returns the correlation coefficient if the class is numeric.
CorrelationSplitInfo class weka.classifiers.trees.m5.CorrelationSplitInfo.Finds split points using correlation.CorrelationSplitInfo(int, int, int).
Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo
Constructs an object which contains the split information
CostCurve class weka.classifiers.evaluation.CostCurve.Generates points illustrating probablity cost tradeoffs that can be
obtained by varying the threshold value between classes.CostCurve().
Constructor for class weka.classifiers.evaluation.CostCurve
CostMatrix class weka.classifiers.CostMatrix.Class for storing and manipulating a misclassification cost matrix.CostMatrix(CostMatrix).
Constructor for class weka.classifiers.CostMatrix
Creates a cost matrix that is a copy of another.
CostMatrix(int).
Constructor for class weka.classifiers.CostMatrix
Creates a default cost matrix of a particular size.
CostMatrix(Reader).
Constructor for class weka.classifiers.CostMatrix
Creates a cost matrix from a reader.
CostMatrixEditor class weka.gui.CostMatrixEditor.Class for editing CostMatrix objects.CostMatrixEditor().
Constructor for class weka.gui.CostMatrixEditor
Constructs a new CostMatrixEditor.
costMatrixSourceTipText().
Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixTipText().
Method in class weka.classifiers.meta.CostSensitiveClassifier
CostSensitiveClassifier class weka.classifiers.meta.CostSensitiveClassifier.This metaclassifier makes its base classifier cost-sensitive.CostSensitiveClassifier().
Constructor for class weka.classifiers.meta.CostSensitiveClassifier
CostSensitiveClassifierSplitEvaluator class weka.experiment.CostSensitiveClassifierSplitEvaluator.A SplitEvaluator that produces results for a classification scheme
on a nominal class attribute, including weighted misclassification costs.CostSensitiveClassifierSplitEvaluator().
Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
count.
Variable in class weka.experiment.PairedStats
The number of data points seen
count.
Variable in class weka.experiment.Stats
The number of values seen
countData().
Method in class weka.classifiers.rules.RuleStats
Filter the data according to the ruleset and compute the basic
stats: coverage/uncoverage, true/false positive/negatives of
each rule
countData(int, Instances, double[][]).
Method in class weka.classifiers.rules.RuleStats
Count data from the position index in the ruleset
assuming that given data are not covered by the rules
in position 0...(index-1), and the statistics of these
rules are provided.
This procedure is typically useful when a temporary
object of RuleStats is constructed in order to efficiently
calculate the relative DL of rule in position index,
thus all other stuff is not needed.
countsForInstance(Instance).
Method in class weka.classifiers.bayes.BayesNet
Calculates the counts for Dirichlet distribution for the
class membership probabilities for the given test instance.
covers(Instance).
Method in class weka.classifiers.rules.Rule
Whether the instance covered by this rule
CramersV(double[][]).
Static method in class weka.core.ContingencyTables
Computes Cramer's V for a contingency table.
create(Reader).
Method in class weka.gui.treevisualizer.TreeBuild
This will build A node structure from the dotty format passed.
createExperimentIndex().
Method in class weka.experiment.DatabaseUtils
Attempts to create the experiment index table
createExperimentIndexEntry(ResultProducer).
Method in class weka.experiment.DatabaseUtils
Attempts to insert a results entry for the table into the
experiment index.
createResultsTable(ResultProducer, String).
Method in class weka.experiment.DatabaseUtils
Creates a results table for the supplied result producer.
crossoverProbTipText().
Method in class weka.attributeSelection.GeneticSearch
Returns the tip text for this property
CrossValidateAttributes().
Method in class weka.attributeSelection.AttributeSelection
Perform a cross validation for attribute selection.
crossValidateModel(Classifier, Instances, int).
Method in class weka.classifiers.Evaluation
Performs a (stratified if class is nominal) cross-validation
for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[]).
Static method in class weka.clusterers.ClusterEvaluation
Performs a cross-validation
for a distribution clusterer on a set of instances.
crossValidateModel(String, Instances, int, String[]).
Method in class weka.classifiers.Evaluation
Performs a (stratified if class is nominal) cross-validation
for a classifier on a set of instances.
CrossValidationFoldMaker class weka.gui.beans.CrossValidationFoldMaker.Bean for splitting instances into training ant test sets according to
a cross validationCrossValidationFoldMaker().
Constructor for class weka.gui.beans.CrossValidationFoldMaker
CrossValidationFoldMakerBeanInfo class weka.gui.beans.CrossValidationFoldMakerBeanInfo.BeanInfo class for the cross validation fold maker beanCrossValidationFoldMakerBeanInfo().
Constructor for class weka.gui.beans.CrossValidationFoldMakerBeanInfo
CrossValidationFoldMakerCustomizer class weka.gui.beans.CrossValidationFoldMakerCustomizer.GUI Customizer for the cross validation fold maker beanCrossValidationFoldMakerCustomizer().
Constructor for class weka.gui.beans.CrossValidationFoldMakerCustomizer
CrossValidationResultProducer class weka.experiment.CrossValidationResultProducer.Generates for each run, carries out an n-fold cross-validation,
using the set SplitEvaluator to generate some results.CrossValidationResultProducer().
Constructor for class weka.experiment.CrossValidationResultProducer
CSVLoader class weka.core.converters.CSVLoader.Reads a text file that is comma or tab delimited..CSVLoader().
Constructor for class weka.core.converters.CSVLoader
CSVResultListener class weka.experiment.CSVResultListener.CSVResultListener outputs the received results in csv format to
a WriterCSVResultListener().
Constructor for class weka.experiment.CSVResultListener
cumulate().
Method in class weka.classifiers.functions.pace.DoubleVector
Returns a vector that stores the cumulated values of the original
vector
cumulateInPlace().
Method in class weka.classifiers.functions.pace.DoubleVector
Cumulates the original vector in place
CustomPanelSupplier interface weka.gui.CustomPanelSupplier.An interface for objects that are capable of supplying their own
custom GUI components.cutoffTipText().
Method in class weka.clusterers.Cobweb
Returns the tip text for this property
CVParameterSelection class weka.classifiers.meta.CVParameterSelection.Class for performing parameter selection by cross-validation for any
classifier.CVParameterSelection().
Constructor for class weka.classifiers.meta.CVParameterSelection
CVResultsString().
Method in class weka.attributeSelection.AttributeSelection
returns a string summarizing the results of repeated attribute
selection runs on splits of a dataset.