/** * 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(); }
/** * Get the number of features used in random selection. * * @return Value of numFeatures. */ public int getNumFeatures() { return ((RandomTree) getClassifier()).getKValue(); }
/** * Set the maximum depth of the tree, 0 for unlimited. * * @param value the maximum depth. */ public void setMaxDepth(int value) { ((RandomTree) getClassifier()).setMaxDepth(value); }
/** * 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(); }
/** * 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(); }
/** * 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); }
/** * Get the maximum depth of trh tree, 0 for unlimited. * * @return the maximum depth. */ public int getMaxDepth() { return ((RandomTree) getClassifier()).getMaxDepth(); }
/** * Get the number of features used in random selection. * * @return Value of numFeatures. */ public int getNumFeatures() { return ((RandomTree) getClassifier()).getKValue(); }
/** * 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(); }
/** * 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); }
/** * 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(); }
/** * Set the maximum depth of the tree, 0 for unlimited. * * @param value the maximum depth. */ public void setMaxDepth(int value) { ((RandomTree) getClassifier()).setMaxDepth(value); }
/** * Get whether to break ties randomly. * * @return true if ties are to be broken randomly. */ public boolean getBreakTiesRandomly() { return ((RandomTree) getClassifier()).getBreakTiesRandomly(); }
/** * 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(); }
/** * Get whether to break ties randomly. * * @return true if ties are to be broken randomly. */ public boolean getBreakTiesRandomly() { return ((RandomTree) getClassifier()).getBreakTiesRandomly(); }
/** * 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); }
/** * 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); }
/** * Set the number of decimal places. */ public void setNumDecimalPlaces(int num) { super.setNumDecimalPlaces(num); ((RandomTree) getClassifier()).setNumDecimalPlaces(num); }
/** * 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); }
/** * Set debugging mode. * * @param debug true if debug output should be printed */ public void setDebug(boolean debug) { super.setDebug(debug); ((RandomTree) getClassifier()).setDebug(debug); }