Package gov.nih.mipav.model.algorithms

Class StochasticForests.Tree

java.lang.Object
gov.nih.mipav.model.algorithms.StochasticForests.Tree
Direct Known Subclasses:
StochasticForests.TreeClassification, StochasticForests.TreeProbability, StochasticForests.TreeRegression, StochasticForests.TreeSurvival
Enclosing class:
StochasticForests
private abstract class StochasticForests.Tree extends Object

  • Field Details

    • random

      protected Random random

    • dependent_varID

      protected int dependent_varID

    • mtry

      protected int mtry

    • num_samples

      protected int num_samples

    • num_samples_oob

      protected int num_samples_oob

    • min_node_size

      protected int min_node_size

    • deterministic_varIDs

      protected Vector<Integer> deterministic_varIDs

    • split_select_varIDs

      protected Vector<Integer> split_select_varIDs

    • split_select_weights

      protected Vector<Double> split_select_weights

    • case_weights

      protected Vector<Double> case_weights

    • split_varIDs

      protected Vector<Integer> split_varIDs

    • split_values

      protected Vector<Double> split_values

    • child_nodeIDs

      protected Vector<Vector<Integer>> child_nodeIDs

    • sampleIDs

      protected Vector<Vector<Integer>> sampleIDs

    • oob_sampleIDs

      protected Vector<Integer> oob_sampleIDs

    • holdout

      protected boolean holdout

    • keep_inbag

      protected boolean keep_inbag

    • inbag_counts

      protected Vector<Integer> inbag_counts

    • data

      protected StochasticForests.Data data

    • variable_importance

      protected Vector<Double> variable_importance

    • importance_mode

      protected StochasticForests.ImportanceMode importance_mode

    • prediction_terminal_nodeIDs

      protected Vector<Integer> prediction_terminal_nodeIDs

    • sample_with_replacement

      protected boolean sample_with_replacement

    • sample_fraction

      protected Vector<Double> sample_fraction

    • memory_saving_splitting

      protected boolean memory_saving_splitting

    • splitrule

      protected StochasticForests.SplitRule splitrule

    • alpha

      protected double alpha

    • minprop

      protected double minprop

    • num_random_splits

      protected int num_random_splits

  • Constructor Details

  • Method Details

    • dispose

      public void dispose()

    • init

      public void init(StochasticForests.Data data, int mtry, int dependent_varID, int num_samples, long seed, Vector<Integer> deterministic_varIDs, Vector<Integer> split_select_varIDs, Vector<Double> split_select_weights, StochasticForests.ImportanceMode importance_mode, int min_node_size, boolean sample_with_replacement, boolean memory_saving_splitting, StochasticForests.SplitRule splitrule, Vector<Double> case_weights, boolean keep_inbag, Vector<Double> sample_fraction, double alpha, double minprop, boolean holdout, int num_random_splits)

    • grow

      public void grow(Vector<Double> variable_importance)

    • predict

      public void predict(StochasticForests.Data prediction_data, boolean oob_prediction)

    • computePermutationImportance

      public void computePermutationImportance(Vector<Double> forest_importance, Vector<Double> forest_variance)

    • appendToFile

      public void appendToFile(BufferedWriter bw)

    • createPossibleSplitVarSubset

      public void createPossibleSplitVarSubset(Vector<Integer> result)

    • splitNode

      public boolean splitNode(int nodeID)

    • createEmptyNode

      public void createEmptyNode()

    • permuteAndPredictOobSamples

      public void permuteAndPredictOobSamples(int permuted_varID, Vector<Integer> permutations)

    • bootstrap

      public void bootstrap()

    • bootstrapWeighted

      public void bootstrapWeighted()

    • bootstrapWithoutReplacement

      public void bootstrapWithoutReplacement()

    • bootstrapWithoutReplacementWeighted

      public void bootstrapWithoutReplacementWeighted()

    • allocateMemory

      public abstract void allocateMemory()

    • appendToFileInternal

      public abstract void appendToFileInternal(BufferedWriter bw)

    • getChildNodeIDs

      public Vector<Vector<Integer>> getChildNodeIDs()

    • getSplitValues

      public Vector<Double> getSplitValues()

    • getSplitVarIDs

      public Vector<Integer> getSplitVarIDs()

    • getOobSampleIDs

      public Vector<Integer> getOobSampleIDs()

    • getNumSamplesOob

      public int getNumSamplesOob()

    • getInbagCounts

      public Vector<Integer> getInbagCounts()

    • splitNodeInternal

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

    • createEmptyNodeInternal

      protected abstract void createEmptyNodeInternal()

    • computePredictionAccuracyInternal

      protected abstract double computePredictionAccuracyInternal()

    • bootstrapClassWise

      protected abstract void bootstrapClassWise()

    • bootstrapWithoutReplacementClassWise

      protected abstract void bootstrapWithoutReplacementClassWise()

    • cleanUpInternal

      protected abstract void cleanUpInternal()