Java weka.classifiers.trees RandomForest fields, constructors, methods, implement or subclass

Example usage for Java weka.classifiers.trees RandomForest fields, constructors, methods, implement or subclass

Introduction

In this page you can find the methods, fields and constructors for weka.classifiers.trees RandomForest.

The text is from its open source code.

	RandomForest() Constructor that sets base classifier for bagging to RandomTre and default number of iterations to 100.

void	buildClassifier(Instances data) Bagging method.
double[]	computeAverageImpurityDecreasePerAttribute(double[] nodeCounts) Computes the average impurity decrease per attribute over the trees
void	main(String[] argv) Main method for this class.
void	setComputeAttributeImportance(boolean computeAttributeImportance) Set whether to compute and output attribute importance scores
void	setMaxDepth(int value) Set the maximum depth of the tree, 0 for unlimited.
void	setNumExecutionSlots(int numSlots) Set the number of execution slots (threads) to use for building the members of the ensemble.
void	setNumFeatures(int newNumFeatures) Set the number of features to use in random selection.
void	setNumIterations(int numIterations) Sets the number of bagging iterations
void	setOptions(String[] options) Parses a given list of options.
void	setSeed(int s) Sets the seed for the random number generator.
String	toString() Returns description of the bagged classifier.