Uses of Class
org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree.Classifier

Packages that use Classifier

Package	Description
org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree

Uses of Classifier in org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree

Subclasses of Classifier in org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree

Modifier and Type	Class	Description
class	J48	Class for generating an unpruned or a pruned C4.5 decision tree.
class	J48WithNDCs	Class for generating an unpruned or a pruned C4.5 decision tree.
class	NaiveBayesSimple	Class for building and using a simple Naive Bayes classifier.

Fields in org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree declared as Classifier

Modifier and Type	Field	Description
static Classifier	Massaging.classifier	Classifier used as Ranker
static Classifier	PrefrentialSamplingFilter.classifier

Methods in org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree that return Classifier

Modifier and Type	Method	Description
static Classifier	Classifier.forName(java.lang.String classifierName, java.lang.String[] options)	Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
static Classifier[]	Classifier.makeCopies(Classifier model, int num)	Creates a given number of deep copies of the given classifier using serialization.
static Classifier	Classifier.makeCopy(Classifier model)	Creates a deep copy of the given classifier using serialization.

Methods in org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree with parameters of type Classifier

Modifier and Type	Method	Description
void	Evaluation.crossValidateModel(Classifier classifier, Instances data, int numFolds, java.util.Random random)	Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
double[]	Evaluation.doEvaluateModelOnce(Classifier classifier, Instance instance)
static java.lang.String	Evaluation.evaluateModel(Classifier classifier, java.lang.String[] options)	Evaluates a classifier with the options given in an array of strings.
double[]	Evaluation.evaluateModel(Classifier classifier, Instances data)	Evaluates the classifier on a given set of instances.
double	Evaluation.evaluateModelOnce(Classifier classifier, Instance instance)
static Classifier[]	Classifier.makeCopies(Classifier model, int num)	Creates a given number of deep copies of the given classifier using serialization.
static Classifier	Classifier.makeCopy(Classifier model)	Creates a deep copy of the given classifier using serialization.
protected static java.lang.String	Evaluation.makeOptionString(Classifier classifier)	Make up the help string giving all the command line options
protected static java.lang.String	Evaluation.printClassifications(Classifier classifier, Instances train, java.lang.String testFileName, int classIndex, Range attributesToOutput)	Prints the predictions for the given dataset into a String variable.
static void	Massaging.setRanker(Classifier classifierName)