Field Detail

• random

  protected java.util.Random random

• verbose_out

  protected boolean verbose_out

• num_trees

  protected int num_trees

• mtry

  protected int mtry

• min_node_size

  protected int min_node_size

• num_variables

  protected int num_variables

• num_independent_variables

  protected int num_independent_variables

• seed

  protected long seed

• dependent_varID

  protected int dependent_varID

• num_samples

  protected int num_samples

• prediction_mode

  protected boolean prediction_mode

• memory_mode

  protected StochasticForests.MemoryMode memory_mode

• sample_with_replacement

  protected boolean sample_with_replacement

• memory_saving_splitting

  protected boolean memory_saving_splitting

• splitrule

  protected StochasticForests.SplitRule splitrule

• predict_all

  protected boolean predict_all

• keep_inbag

  protected boolean keep_inbag

• sample_fraction

  protected java.util.Vector<java.lang.Double> sample_fraction

• holdout

  protected boolean holdout

• prediction_type

  protected StochasticForests.PredictionType prediction_type

• num_random_splits

  protected int num_random_splits

• alpha

  protected double alpha

• minprop

  protected double minprop

• num_threads

  protected int num_threads

• thread_ranges

  protected java.util.Vector<java.lang.Integer> thread_ranges

• trees

  protected java.util.Vector<StochasticForests.Tree> trees

• data

  protected StochasticForests.Data data

• predictions

  protected java.util.Vector<java.util.Vector<java.util.Vector<java.lang.Double>>> predictions

• overall_prediction_error

  protected double overall_prediction_error

• deterministic_varIDs

  protected java.util.Vector<java.lang.Integer> deterministic_varIDs

• split_select_varIDs

  protected java.util.Vector<java.lang.Integer> split_select_varIDs

• split_select_weights

  protected java.util.Vector<java.util.Vector<java.lang.Double>> split_select_weights

• case_weights

  protected java.util.Vector<java.lang.Double> case_weights

• output_prefix

  protected java.lang.String output_prefix

• importance_mode

  protected StochasticForests.ImportanceMode importance_mode

• variable_importance

  protected java.util.Vector<java.lang.Double> variable_importance

• progress

  protected int progress

• mutex

  protected final java.util.concurrent.locks.Lock mutex

• condition_variable

  private final java.util.concurrent.locks.Condition condition_variable

Constructor Detail

• Forest

  public Forest()

Method Detail

• growInternal

  protected abstract void growInternal()

• allocatePredictMemory

  protected abstract void allocatePredictMemory()

• predictInternal

  protected abstract void predictInternal​(int sample_idx)

• computePredictionErrorInternal

  protected abstract void computePredictionErrorInternal()

• loadFromFileInternal

  protected abstract void loadFromFileInternal​(java.io.BufferedReader br)

• initInternal

  public abstract void initInternal​(java.lang.String status_variable_name)

• writeOutputInternal

  public abstract void writeOutputInternal()

• writeConfusionFile

  public abstract void writeConfusionFile()

• writePredictionFile

  public abstract void writePredictionFile()

• saveToFileInternal

  public abstract void saveToFileInternal​(java.io.BufferedWriter bw)

• getChildNodeIDs

  public java.util.Vector<java.util.Vector<java.util.Vector<java.lang.Integer>>> getChildNodeIDs()

• getSplitVarIDs

  public java.util.Vector<java.util.Vector<java.lang.Integer>> getSplitVarIDs()

• getSplitValues

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

• getVariableImportance

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

• getOverallPredictionError

  public double getOverallPredictionError()

• getPredictions

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

• getDependentVarId

  public int getDependentVarId()

• getNumTrees

  public int getNumTrees()

• getMtry

  public int getMtry()

• getMinNodeSize

  public int getMinNodeSize()

• getNumIndependentVariables

  public int getNumIndependentVariables()

• getIsOrderedVariable

  public java.util.Vector<java.lang.Boolean> getIsOrderedVariable()

• getInbagCounts

  public java.util.Vector<java.util.Vector<java.lang.Integer>> getInbagCounts()

• dispose

  public void dispose()

• initCpp

  public void initCpp​(java.lang.String dependent_variable_name,
                      StochasticForests.MemoryMode memory_mode,
                      java.lang.String input_file,
                      int mtry,
                      java.lang.String output_prefix,
                      int num_trees,
                      boolean verbose_out,
                      long seed,
                      int num_threads,
                      java.lang.String load_forest_filename,
                      StochasticForests.ImportanceMode importance_mode,
                      int min_node_size,
                      java.lang.String split_select_weights_file,
                      java.util.Vector<java.lang.String> always_split_variable_names,
                      java.lang.String status_variable_name,
                      boolean sample_with_replacement,
                      java.util.Vector<java.lang.String> unordered_variable_names,
                      boolean memory_saving_splitting,
                      StochasticForests.SplitRule splitrule,
                      java.lang.String case_weights_file,
                      boolean predict_all,
                      double sample_fraction,
                      double alpha,
                      double minprop,
                      boolean holdout,
                      StochasticForests.PredictionType prediction_type,
                      int num_random_splits)

• initR

  public void initR​(java.lang.String dependent_variable_name,
                    StochasticForests.Data input_data,
                    int mtry,
                    int num_trees,
                    boolean verbose_out,
                    long seed,
                    int num_threads,
                    StochasticForests.ImportanceMode importance_mode,
                    int min_node_size,
                    java.util.Vector<java.util.Vector<java.lang.Double>> split_select_weights,
                    java.util.Vector<java.lang.String> always_split_variable_names,
                    java.lang.String status_variable_name,
                    boolean prediction_mode,
                    boolean sample_with_replacement,
                    java.util.Vector<java.lang.String> unordered_variable_names,
                    boolean memory_saving_splitting,
                    StochasticForests.SplitRule splitrule,
                    java.util.Vector<java.lang.Double> case_weights,
                    boolean predict_all,
                    boolean keep_inbag,
                    java.util.Vector<java.lang.Double> sample_fraction,
                    double alpha,
                    double minprop,
                    boolean holdout,
                    StochasticForests.PredictionType prediction_type,
                    int num_random_splits)

• init

  public void init​(java.lang.String dependent_variable_name,
                   StochasticForests.MemoryMode memory_mode,
                   StochasticForests.Data input_data,
                   int mtry,
                   java.lang.String output_prefix,
                   int num_trees,
                   long seed,
                   int num_threads,
                   StochasticForests.ImportanceMode importance_mode,
                   int min_node_size,
                   java.lang.String status_variable_name,
                   boolean prediction_mode,
                   boolean sample_with_replacement,
                   java.util.Vector<java.lang.String> unordered_variable_names,
                   boolean memory_saving_splitting,
                   StochasticForests.SplitRule splitrule,
                   boolean predict_all,
                   java.util.Vector<java.lang.Double> sample_fraction,
                   double alpha,
                   double minprop,
                   boolean holdout,
                   StochasticForests.PredictionType prediction_type,
                   int num_random_splits)

• run

  public void run​(boolean verbose)

• writeOutput

  public void writeOutput()

• writeImportanceFile

  public void writeImportanceFile()

• saveToFile

  public void saveToFile()

• grow

  public void grow()

• predict

  public void predict()

• computePredictionError

  public void computePredictionError()

• computePermutationImportance

  public void computePermutationImportance()

• loadFromFile

  public void loadFromFile​(java.lang.String filename)

• setSplitWeightVector

  public void setSplitWeightVector​(java.util.Vector<java.util.Vector<java.lang.Double>> split_select_weights)

• setAlwaysSplitVariables

  public void setAlwaysSplitVariables​(java.util.Vector<java.lang.String> always_split_variable_names)