Package gov.nih.mipav.model.algorithms

Class StochasticForests.TreeProbability

java.lang.Object

gov.nih.mipav.model.algorithms.StochasticForests.Tree

gov.nih.mipav.model.algorithms.StochasticForests.TreeProbability

Enclosing class:

StochasticForests

private class StochasticForests.TreeProbability
extends StochasticForests.Tree

Field Summary

Fields

Modifier and Type	Field	Description
(package private) Vector<Double>	class_values
(package private) Vector<Double>	class_weights
(package private) int[]	counter
(package private) int[]	counter_per_class
(package private) Vector<Integer>	response_classIDs
(package private) Vector<Vector<Integer>>	sampleIDs_per_class
(package private) Vector<Vector<Double>>	terminal_class_counts

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

alpha, case_weights, child_nodeIDs, data, dependent_varID, deterministic_varIDs, holdout, importance_mode, inbag_counts, keep_inbag, memory_saving_splitting, min_node_size, minprop, mtry, num_random_splits, num_samples, num_samples_oob, oob_sampleIDs, prediction_terminal_nodeIDs, random, sample_fraction, sample_with_replacement, sampleIDs, split_select_varIDs, split_select_weights, split_values, split_varIDs, splitrule, variable_importance

Constructor Summary

Constructors

Constructor	Description
TreeProbability(Vector<Double> class_values, Vector<Integer> response_classIDs, Vector<Vector<Integer>> sampleIDs_per_class, Vector<Double> class_weights)
TreeProbability(Vector<Vector<Integer>> child_nodeIDs, Vector<Integer> split_varIDs, Vector<Double> split_values, Vector<Double> class_values, Vector<Integer> response_classIDs, Vector<Vector<Double>> terminal_class_counts)

Method Summary

Modifier and Type	Method	Description
void	addImpurityImportance(int nodeID, int varID, double decrease)
void	addToTerminalNodes(int nodeID)
void	allocateMemory()
void	appendToFileInternal(BufferedWriter bw)
void	bootstrapClassWise()
void	bootstrapWithoutReplacementClassWise()
void	cleanUpInternal()
double	computePredictionAccuracyInternal()
void	createEmptyNodeInternal()
boolean	findBestSplit(int nodeID, Vector<Integer> possible_split_varIDs)
boolean	findBestSplitExtraTrees(int nodeID, Vector<Integer> possible_split_varIDs)
void	findBestSplitValueExtraTrees(int nodeID, int varID, int num_classes, int[] class_counts, int num_samples_node, double[] best_value, int[] best_varID, double[] best_decrease)
void	findBestSplitValueExtraTreesUnordered(int nodeID, int varID, int num_classes, int[] class_counts, int num_samples_node, double[] best_value, int[] best_varID, double[] best_decrease)
void	findBestSplitValueLargeQ(int nodeID, int varID, int num_classes, int[] class_counts, int num_samples_node, double[] best_value, int[] best_varID, double[] best_decrease)
void	findBestSplitValueSmallQ(int nodeID, int varID, int num_classes, int[] class_counts, int num_samples_node, double[] best_value, int[] best_varID, double[] best_decrease)
void	findBestSplitValueUnordered(int nodeID, int varID, int num_classes, int[] class_counts, int num_samples_node, double[] best_value, int[] best_varID, double[] best_decrease)
Vector<Double>	getPrediction(int sampleID)
int	getPredictionTerminalNodeID(int sampleID)
Vector<Vector<Double>>	getTerminalClassCounts()
boolean	splitNodeInternal(int nodeID, Vector<Integer> possible_split_varIDs)

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

appendToFile, bootstrap, bootstrapWeighted, bootstrapWithoutReplacement, bootstrapWithoutReplacementWeighted, computePermutationImportance, createEmptyNode, createPossibleSplitVarSubset, dispose, dropDownSamplePermuted, getChildNodeIDs, getInbagCounts, getNumSamplesOob, getOobSampleIDs, getSplitValues, getSplitVarIDs, grow, init, permuteAndPredictOobSamples, predict, splitNode

Methods inherited from class java.lang.Object

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

Field Details

class_values

Vector<Double> class_values

response_classIDs

Vector<Integer> response_classIDs

sampleIDs_per_class

Vector<Vector<Integer>> sampleIDs_per_class

terminal_class_counts

Vector<Vector<Double>> terminal_class_counts

class_weights

Vector<Double> class_weights

counter

int[] counter

counter_per_class

int[] counter_per_class

Constructor Details

TreeProbability

public TreeProbability(Vector<Double> class_values,
 Vector<Integer> response_classIDs,
 Vector<Vector<Integer>> sampleIDs_per_class,
 Vector<Double> class_weights)

TreeProbability

public TreeProbability(Vector<Vector<Integer>> child_nodeIDs,
 Vector<Integer> split_varIDs,
 Vector<Double> split_values,
 Vector<Double> class_values,
 Vector<Integer> response_classIDs,
 Vector<Vector<Double>> terminal_class_counts)

Method Details

cleanUpInternal

public void cleanUpInternal()

Specified by:

cleanUpInternal in class StochasticForests.Tree

getPrediction

public Vector<Double> getPrediction(int sampleID)

getPredictionTerminalNodeID

public int getPredictionTerminalNodeID(int sampleID)

getTerminalClassCounts

public Vector<Vector<Double>> getTerminalClassCounts()

allocateMemory

public void allocateMemory()

Specified by:

allocateMemory in class StochasticForests.Tree

addToTerminalNodes

public void addToTerminalNodes(int nodeID)

appendToFileInternal

public void appendToFileInternal(BufferedWriter bw)

Specified by:

appendToFileInternal in class StochasticForests.Tree

splitNodeInternal

public boolean splitNodeInternal(int nodeID,
 Vector<Integer> possible_split_varIDs)

Specified by:

splitNodeInternal in class StochasticForests.Tree

createEmptyNodeInternal

public void createEmptyNodeInternal()

Specified by:

createEmptyNodeInternal in class StochasticForests.Tree

computePredictionAccuracyInternal

public double computePredictionAccuracyInternal()

Specified by:

computePredictionAccuracyInternal in class StochasticForests.Tree

findBestSplit

public boolean findBestSplit(int nodeID,
 Vector<Integer> possible_split_varIDs)

findBestSplitValueSmallQ

public void findBestSplitValueSmallQ(int nodeID,
 int varID,
 int num_classes,
 int[] class_counts,
 int num_samples_node,
 double[] best_value,
 int[] best_varID,
 double[] best_decrease)

findBestSplitValueLargeQ

public void findBestSplitValueLargeQ(int nodeID,
 int varID,
 int num_classes,
 int[] class_counts,
 int num_samples_node,
 double[] best_value,
 int[] best_varID,
 double[] best_decrease)

findBestSplitValueUnordered

public void findBestSplitValueUnordered(int nodeID,
 int varID,
 int num_classes,
 int[] class_counts,
 int num_samples_node,
 double[] best_value,
 int[] best_varID,
 double[] best_decrease)

findBestSplitExtraTrees

public boolean findBestSplitExtraTrees(int nodeID,
 Vector<Integer> possible_split_varIDs)

findBestSplitValueExtraTrees

public void findBestSplitValueExtraTrees(int nodeID,
 int varID,
 int num_classes,
 int[] class_counts,
 int num_samples_node,
 double[] best_value,
 int[] best_varID,
 double[] best_decrease)

findBestSplitValueExtraTreesUnordered

public void findBestSplitValueExtraTreesUnordered(int nodeID,
 int varID,
 int num_classes,
 int[] class_counts,
 int num_samples_node,
 double[] best_value,
 int[] best_varID,
 double[] best_decrease)

addImpurityImportance

public void addImpurityImportance(int nodeID,
 int varID,
 double decrease)

bootstrapClassWise

public void bootstrapClassWise()

Specified by:

bootstrapClassWise in class StochasticForests.Tree

bootstrapWithoutReplacementClassWise

public void bootstrapWithoutReplacementClassWise()

Specified by:

bootstrapWithoutReplacementClassWise in class StochasticForests.Tree