Examples of weka.classifiers.trees.M5P

weka.classifiers.trees.M5P

M5Base. Implements base routines for generating M5 Model trees and rules
The original algorithm M5 was invented by R. Quinlan and Yong Wang made improvements.

For more information see:

Ross J. Quinlan: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence, Singapore, 343-348, 1992.

Y. Wang, I. H. Witten: Induction of model trees for predicting continuous classes. In: Poster papers of the 9th European Conference on Machine Learning, 1997.

BibTeX:

 @inproceedings{Quinlan1992, address = {Singapore}, author = {Ross J. Quinlan}, booktitle = {5th Australian Joint Conference on Artificial Intelligence}, pages = {343-348}, publisher = {World Scientific}, title = {Learning with Continuous Classes}, year = {1992} } @inproceedings{Wang1997, author = {Y. Wang and I. H. Witten}, booktitle = {Poster papers of the 9th European Conference on Machine Learning}, publisher = {Springer}, title = {Induction of model trees for predicting continuous classes}, year = {1997} }

Valid options are:

 -N Use unpruned tree/rules

 -U Use unsmoothed predictions

 -R Build regression tree/rule rather than a model tree/rule

 -M <minimum number of instances> Set minimum number of instances per leaf (default 4)

 -L Save instances at the nodes in the tree (for visualization purposes)

@author Mark Hall @version $Revision: 1.10 $

      // E.g., the XRFF format saves the class attribute information as well
      if (data.classIndex() == -1)
        data.setClass(data.attribute(attribute));
      
      // train M5P
      cl = new M5P();
      cl.setBuildRegressionTree(true);
      cl.setUnpruned(false);
      cl.setUseUnsmoothed(false);
      // further options...
      cl.buildClassifier(data);

        String[] argv  = new String[2];
        argv[0] = "-t";
        //argv[1] = "d:/weather.arff";
        //sbWeka.append(Evaluation.evaluateModel(new J48(), argv));
        argv[1] = "d:/cpu.arff"; 
        sbWeka.append(Evaluation.evaluateModel(new M5P(), argv));
        } catch (Exception e) {
          sbWeka.append(e.getMessage());
        }
    Map<String, Object> myModel = new HashMap<String, Object>();
    myModel.put("weka", sbWeka);

Examples of weka.classifiers.trees.M5P

Related Classes of weka.classifiers.trees.M5P