Examples of REPTree

• weka.classifiers.trees.REPTree
  Fast decision tree learner. Builds a decision/regression tree using information gain/variance and prunes it using reduced-error pruning (with backfitting). Only sorts values for numeric attributes once. Missing values are dealt with by splitting the corresponding instances into pieces (i.e. as in C4.5).

  Valid options are:

   -M <minimum number of instances> Set minimum number of instances per leaf (default 2).

   -V <minimum variance for split> Set minimum numeric class variance proportion of train variance for split (default 1e-3).

   -N <number of folds> Number of folds for reduced error pruning (default 3).

   -S <seed> Seed for random data shuffling (default 1).

   -P No pruning.

   -L Maximum tree depth (default -1, no maximum)

  @author Eibe Frank (eibe@cs.waikato.ac.nz) @version $Revision: 6952 $

Examples of weka.classifiers.trees.REPTree