www.pudn.com > id3ClaafierTreeCode.rar > TDDTOptions.java

package id3; 
/** This class stores information about option settings for Top-Down Decision 
 * Tree inducers. 
 * @author James Louis   Ported to Java 
 */ 
public class TDDTOptions { 
     
    /** The maximum level of growth. 
     */ 
    public int maxLevel; 
     
    /** The lower bound for the minimum weight of instances in a node. 
     * 
     */ 
    public double lowerBoundMinSplitWeight; 
     /** The upper bound for the minimum weight of instances in a node. 
      */ 
    public double upperBoundMinSplitWeight; 
     
    /** The percent (p) used to calculate the min weight of instances in a node (m). 
 
     * m = p * num instances / num categories 
     * 
     */ 
    public double minSplitWeightPercent; 
     
    /** TRUE indicates lowerBoundMinSplitWeight, upperBoundMinSplitWeight, and 
     * minSplitWeightPercent are not used for setting minimum instances in a node for 
     * nominal attributes, FALSE indicates they will be used. 
     */ 
    public boolean nominalLBoundOnly; 
     
    /** TRUE if debugging options are used. 
     */ 
    public boolean debug; 
     
    /** TRUE indicates there will be an edge with "unknown" from every node. 
     * 
     */ 
    public boolean unknownEdges; 
     
    /** The criterion used for scoring. 
     */     
    public byte splitScoreCriterion; 
     
    /** TRUE indicates an empty node should have the parent's distribution, FALSE 
     * otherwise. 
     * 
     */     
    public boolean emptyNodeParentDist; 
     
    /** TRUE indicates a node should inherit the parent's tie-breaking class, FALSE 
     * otherwise. 
     * 
     */     
    public boolean parentTieBreaking; 
     
    /** Pruning method to be used. If the value is not NONE and pruning_factor is 0, 
     * then a node will be made a leaf when its (potential) children do not improve 
     * the error count. 
     * 
     */ 
    public byte pruningMethod; 
     
    /** TRUE indicates pruning should allow replacing a node with its largest subtree, 
     * FALSE otherwise. 
     * 
     */     
    public boolean pruningBranchReplacement; 
     
    /** TRUE indicates threshold should be adjusted to equal instance values, FALSE 
     * otherwise. 
     * 
     */     
    public boolean adjustThresholds; 
     
    /** Factor of how much pruning should be done. High values indicate more pruning. 
     */ 
    public double pruningFactor; 
     
    /** TRUE if the Minimum Description Length Adjustment for continuous attributes should 
     * be applied to mutual info, FALSE otherwise. 
     * 
     */     
    public boolean contMDLAdjust; 
     
    /** Number of thresholds on either side to use for smoothing; 0 for no smoothing. 
     * 
     */     
    public int smoothInst; 
     
    /** Exponential factor for smoothing. 
     */     
    public double smoothFactor; 
     
    /** Type of distribution to build at leaves. 
     * 
     */ 
    public byte leafDistType; 
     
    /** M-estimate factor for laplace. 
     */ 
    public double MEstimateFactor; 
     
    /** Evidence correction factor. 
     */ 
    public double evidenceFactor; 
     
    /** The metric used to evaluate this decision tree. 
     * 
     */ 
    public byte evaluationMetric; 
     
    /** Constructor. 
     */ 
    public TDDTOptions(){} 
     
}