Package gov.nih.mipav.model.algorithms

Class StochasticForests.ForestClassification

java.lang.Object

gov.nih.mipav.model.algorithms.StochasticForests.Forest

gov.nih.mipav.model.algorithms.StochasticForests.ForestClassification

Enclosing class:

StochasticForests

private class StochasticForests.ForestClassification
extends StochasticForests.Forest

Nested Class Summary

Nested classes/interfaces inherited from class gov.nih.mipav.model.algorithms.StochasticForests.Forest

StochasticForests.Forest.computeTreePermutationImportanceInThread, StochasticForests.Forest.growTreesInThread, StochasticForests.Forest.predictInternalInThread, StochasticForests.Forest.predictTreesInThread, StochasticForests.Forest.showProgress

Field Summary

Fields

Modifier and Type	Field	Description
(package private) java.util.Vector<java.lang.Double>	class_values
(package private) java.util.Vector<java.lang.Double>	class_weights
(package private) java.util.HashMap<StochasticForests.ValuePair<java.lang.Double,java.lang.Double>,java.lang.Integer>	classification_table
(package private) java.util.Vector<java.lang.Integer>	response_classIDs
(package private) java.util.Vector<java.util.Vector<java.lang.Integer>>	sampleIDs_per_class

Fields inherited from class gov.nih.mipav.model.algorithms.StochasticForests.Forest

alpha, case_weights, data, dependent_varID, deterministic_varIDs, holdout, importance_mode, keep_inbag, memory_mode, memory_saving_splitting, min_node_size, minprop, mtry, mutex, num_independent_variables, num_random_splits, num_samples, num_threads, num_trees, num_variables, output_prefix, overall_prediction_error, predict_all, prediction_mode, prediction_type, predictions, progress, random, sample_fraction, sample_with_replacement, seed, split_select_varIDs, split_select_weights, splitrule, thread_ranges, trees, variable_importance, verbose_out

Constructor Summary

Constructors

Constructor	Description
ForestClassification()

Method Summary

Modifier and Type	Method	Description
void	allocatePredictMemory()
void	computePredictionErrorInternal()
java.util.Vector<java.lang.Double>	getClassValues()
void	growInternal()
void	initInternal(java.lang.String status_variable_name)
void	loadForest(int dependent_varID, int num_trees, java.util.Vector<java.util.Vector<java.util.Vector<java.lang.Integer>>> forest_child_nodeIDs, java.util.Vector<java.util.Vector<java.lang.Integer>> forest_split_varIDs, java.util.Vector<java.util.Vector<java.lang.Double>> forest_split_values, java.util.Vector<java.lang.Double> class_values, java.util.Vector<java.lang.Boolean> is_ordered_variable)
void	loadFromFileInternal(java.io.BufferedReader br)
void	predictInternal(int sample_idx)
void	saveToFileInternal(java.io.BufferedWriter bw)
void	setClassWeights(java.util.Vector<java.lang.Double> class_weights)
void	writeConfusionFile()
void	writeOutputInternal()
void	writePredictionFile()

Methods inherited from class gov.nih.mipav.model.algorithms.StochasticForests.Forest

computePermutationImportance, computePredictionError, dispose, getChildNodeIDs, getDependentVarId, getInbagCounts, getIsOrderedVariable, getMinNodeSize, getMtry, getNumIndependentVariables, getNumTrees, getOverallPredictionError, getPredictions, getSplitValues, getSplitVarIDs, getVariableImportance, grow, init, initCpp, initR, loadFromFile, predict, run, saveToFile, setAlwaysSplitVariables, setSplitWeightVector, writeImportanceFile, writeOutput

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

class_values

java.util.Vector<java.lang.Double> class_values

response_classIDs

java.util.Vector<java.lang.Integer> response_classIDs

sampleIDs_per_class

java.util.Vector<java.util.Vector<java.lang.Integer>> sampleIDs_per_class

class_weights

java.util.Vector<java.lang.Double> class_weights

classification_table

java.util.HashMap<StochasticForests.ValuePair<java.lang.Double,java.lang.Double>,java.lang.Integer> classification_table

Constructor Detail

ForestClassification

public ForestClassification()

Method Detail

getClassValues

public java.util.Vector<java.lang.Double> getClassValues()

setClassWeights

public void setClassWeights(java.util.Vector<java.lang.Double> class_weights)

loadForest

public void loadForest(int dependent_varID,
                       int num_trees,
                       java.util.Vector<java.util.Vector<java.util.Vector<java.lang.Integer>>> forest_child_nodeIDs,
                       java.util.Vector<java.util.Vector<java.lang.Integer>> forest_split_varIDs,
                       java.util.Vector<java.util.Vector<java.lang.Double>> forest_split_values,
                       java.util.Vector<java.lang.Double> class_values,
                       java.util.Vector<java.lang.Boolean> is_ordered_variable)

initInternal

public void initInternal(java.lang.String status_variable_name)

Specified by:

initInternal in class StochasticForests.Forest

growInternal

public void growInternal()

Specified by:

growInternal in class StochasticForests.Forest

allocatePredictMemory

public void allocatePredictMemory()

Specified by:

allocatePredictMemory in class StochasticForests.Forest

predictInternal

public void predictInternal(int sample_idx)

Specified by:

predictInternal in class StochasticForests.Forest

computePredictionErrorInternal

public void computePredictionErrorInternal()

Specified by:

computePredictionErrorInternal in class StochasticForests.Forest

writeOutputInternal

public void writeOutputInternal()

Specified by:

writeOutputInternal in class StochasticForests.Forest

writeConfusionFile

public void writeConfusionFile()

Specified by:

writeConfusionFile in class StochasticForests.Forest

writePredictionFile

public void writePredictionFile()

Specified by:

writePredictionFile in class StochasticForests.Forest

saveToFileInternal

public void saveToFileInternal(java.io.BufferedWriter bw)

Specified by:

saveToFileInternal in class StochasticForests.Forest

loadFromFileInternal

public void loadFromFileInternal(java.io.BufferedReader br)

Specified by:

loadFromFileInternal in class StochasticForests.Forest