hr.irb.fastRandomForest (Fiji Javadocs 0-SNAPSHOT API)

Class Summary
Class	Description
Benchmark	Runs 10 iterations of 10-fold crossvalidation on the supplied arff file(s) using weka.classifiers.trees.RandomForest, and FastRandomForest, and prints accuracy, AUC (averaged over all classes) and computation time to stdout.
DataCache	Stores a dataset that in FastRandomTrees use for training.
FastRandomForest	Based on the "weka.classifiers.trees.RandomForest" class, revision 1.12, by Richard Kirkby, with minor modifications: uses FastRfBagger with FastRandomTree, instead of Bagger with RandomTree. stores dataset header (instead of every Tree storing its own header) checks if only ZeroR model is possible (instead of each Tree checking) added "-threads" option
FastRfUtils	Utility functions for sorting float (single-precision) arrays, and for normalizing double arrays.
FRFAttributeEval	Evaluate the merit of each attribute using a random forest.
SplitCriteria	Functions used for finding best splits in FastRfTree.
VotesCollector	Used to retrieve the out-of-bag vote of an ensemble classifier for a single instance.
VotesCollectorDataCache	Used to retrieve the out-of-bag vote of an FastRandomForest classifier for a single instance from a DataCache the forest was trained on.

Package hr.irb.fastRandomForest