J48 model=new J48(); model.buildClassifier(test);
/** * 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); }
/** * 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(); }
/** * 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(); }
/** * 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); }
/** * Builds the classifier to generate a partition. */ @Override public void generatePartition(Instances data) throws Exception { buildClassifier(data); }
/** * 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); }
/** * 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(); }
/** * 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(); }
/** * 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); }