Documentation of 'cc.mallet.classify.C45Trainer' Java class
C45Trainer
cc.mallet.classify

Class C45Trainer

  • All Implemented Interfaces:
    Boostable


    public class C45Trainer
    extends ClassifierTrainer<C45>
    implements Boostable
    A C4.5 decision tree learner, approximtely. Currently treats all features as continuous-valued, and has no notion of missing values.

    This implementation uses MDL for pruning.

    J. R. Quinlan
    "Improved Use of Continuous Attributes in C4.5"
    ftp://ftp.cs.cmu.edu/project/jair/volume4/quinlan96a.ps

    J. R. Quinlan and R. L. Rivest
    "Inferring Decision Trees Using Minimum Description Length Principle"

    • Constructor Detail

      • C45Trainer

        public C45Trainer()
        Uses default values: not depth limited tree with a minimum of 2 instances in each leaf node
      • C45Trainer

        public C45Trainer(int maxDepth)
        Construct a depth-limited tree with the given depth limit
      • C45Trainer

        public C45Trainer(boolean doPruning)
      • C45Trainer

        public C45Trainer(int maxDepth,
                          boolean doPruning)
    • Method Detail

      • setDoPruning

        public void setDoPruning(boolean doPruning)
      • getDoPruning

        public boolean getDoPruning()
      • setDepthLimited

        public void setDepthLimited(boolean depthLimited)
      • getDepthLimited

        public boolean getDepthLimited()
      • setMaxDepth

        public void setMaxDepth(int maxDepth)
      • getMaxDepth

        public int getMaxDepth()
      • setMinNumInsts

        public void setMinNumInsts(int minNumInsts)
      • getMinNumInsts

        public int getMinNumInsts()

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