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RandomForest.getClassifier
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How to use
getClassifier
method
in
weka.classifiers.trees.RandomForest

Best Java code snippets using weka.classifiers.trees.RandomForest.getClassifier (Showing top 20 results out of 315)

origin: Waikato/weka-trunk

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String breakTiesRandomlyTipText() {
 return ((RandomTree) getClassifier()).breakTiesRandomlyTipText();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Get the number of features used in random selection.
 *
 * @return Value of numFeatures.
 */
public int getNumFeatures() {
 return ((RandomTree) getClassifier()).getKValue();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set the maximum depth of the tree, 0 for unlimited.
 *
 * @param value the maximum depth.
 */
public void setMaxDepth(int value) {
 ((RandomTree) getClassifier()).setMaxDepth(value);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String breakTiesRandomlyTipText() {
 return ((RandomTree) getClassifier()).breakTiesRandomlyTipText();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String numFeaturesTipText() {
 return ((RandomTree) getClassifier()).KValueTipText();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set the number of features to use in random selection.
 *
 * @param newNumFeatures Value to assign to numFeatures.
 */
public void setNumFeatures(int newNumFeatures) {
 ((RandomTree) getClassifier()).setKValue(newNumFeatures);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Get the maximum depth of trh tree, 0 for unlimited.
 *
 * @return the maximum depth.
 */
public int getMaxDepth() {
 return ((RandomTree) getClassifier()).getMaxDepth();
}
origin: Waikato/weka-trunk

/**
 * Get the number of features used in random selection.
 *
 * @return Value of numFeatures.
 */
public int getNumFeatures() {
 return ((RandomTree) getClassifier()).getKValue();
}
origin: Waikato/weka-trunk

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String numFeaturesTipText() {
 return ((RandomTree) getClassifier()).KValueTipText();
}
origin: Waikato/weka-trunk

/**
 * Set the number of features to use in random selection.
 *
 * @param newNumFeatures Value to assign to numFeatures.
 */
public void setNumFeatures(int newNumFeatures) {
 ((RandomTree) getClassifier()).setKValue(newNumFeatures);
}
origin: Waikato/weka-trunk

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String maxDepthTipText() {
 return ((RandomTree) getClassifier()).maxDepthTipText();
}
origin: Waikato/weka-trunk

/**
 * Set the maximum depth of the tree, 0 for unlimited.
 *
 * @param value the maximum depth.
 */
public void setMaxDepth(int value) {
 ((RandomTree) getClassifier()).setMaxDepth(value);
}
origin: Waikato/weka-trunk

/**
 * Get whether to break ties randomly.
 *
 * @return true if ties are to be broken randomly.
 */
public boolean getBreakTiesRandomly() {
 return ((RandomTree) getClassifier()).getBreakTiesRandomly();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Returns the tip text for this property
 *
 * @return tip text for this property suitable for displaying in the
 *         explorer/experimenter gui
 */
public String maxDepthTipText() {
 return ((RandomTree) getClassifier()).maxDepthTipText();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Get whether to break ties randomly.
 *
 * @return true if ties are to be broken randomly.
 */
public boolean getBreakTiesRandomly() {
 return ((RandomTree) getClassifier()).getBreakTiesRandomly();
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set whether to break ties randomly.
 *
 * @param newBreakTiesRandomly true if ties are to be broken randomly
 */
public void setBreakTiesRandomly(boolean newBreakTiesRandomly) {
 ((RandomTree) getClassifier()).setBreakTiesRandomly(newBreakTiesRandomly);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Sets the seed for the random number generator.
 *
 * @param s the seed to be used
 */
public void setSeed(int s) {
 super.setSeed(s);
 ((RandomTree) getClassifier()).setSeed(s);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set the number of decimal places.
 */
public void setNumDecimalPlaces(int num) {
 super.setNumDecimalPlaces(num);
 ((RandomTree) getClassifier()).setNumDecimalPlaces(num);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set the preferred batch size for batch prediction.
 *
 * @param size the batch size to use
 */
@Override
public void setBatchSize(String size) {
 super.setBatchSize(size);
 ((RandomTree) getClassifier()).setBatchSize(size);
}
origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Set debugging mode.
 *
 * @param debug true if debug output should be printed
 */
public void setDebug(boolean debug) {
 super.setDebug(debug);
 ((RandomTree) getClassifier()).setDebug(debug);
}
weka.classifiers.treesRandomForestgetClassifier

Popular methods of RandomForest

  • <init>
    Constructor that sets base classifier for bagging to RandomTre and default number of iterations to 1
  • computeAverageImpurityDecreasePerAttribute
    Computes the average impurity decrease per attribute over the trees
  • defaultClassifierString
    String describing default classifier.
  • defaultNumberOfIterations
    The default number of iterations to perform.
  • getBagSizePercent
  • getCalcOutOfBag
  • getComputeAttributeImportance
    Get whether to compute and output attribute importance scores
  • getDoNotCheckCapabilities
  • getNumDecimalPlaces
  • getNumExecutionSlots
  • getNumIterations
  • getOutputOutOfBagComplexityStatistics
  • getNumIterations,
  • getOutputOutOfBagComplexityStatistics,
  • getPrintClassifiers,
  • getStoreOutOfBagPredictions,
  • getTechnicalInformation,
  • runClassifier,
  • setBagSizePercent,
  • setBatchSize,
  • setCalcOutOfBag

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