Examples of weka.classifiers.misc.InputMappedClassifier

weka.classifiers.misc.InputMappedClassifier

Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure. Model attributes that are not found in the incoming instances receive missing values, so do incoming nominal attribute values that the classifier has not seen before. A new classifier can be trained or an existing one loaded from a file.

Valid options are:

 -I Ignore case when matching attribute names and nominal values.

 -M Suppress the output of the mapping report.

 -trim Trim white space from either end of names before matching.

 -L <path to model to load> Path to a model to load. If set, this model will be used for prediction and any base classifier specification will be ignored. Environment variables may be used in the path (e.g. ${HOME}/myModel.model)

 -D If set, classifier is run in debug mode and may output additional info to the console

 -W Full name of base classifier. (default: weka.classifiers.rules.ZeroR)

  Options specific to classifier weka.classifiers.rules.ZeroR:

 -D If set, classifier is run in debug mode and may output additional info to the console

@author Mark Hall (mhall{[at]}pentaho{[dot]}com) @version $Revision: 6893 $


  public InputMappedClassifierTest(String name) { super(name);  }


  /** Creates a default InputMappedClassifier */
  public Classifier getClassifier() {
    InputMappedClassifier toUse = new InputMappedClassifier();
    toUse.setClassifier(new weka.classifiers.trees.J48());
    toUse.setSuppressMappingReport(true);
    return toUse;
  }

      } catch (Exception ex) {
        fail("Reordering test data failed: " + ex);
      }
    }
    
    InputMappedClassifier toUse = null;
    
    try {
      toUse = trainClassifier(train, nomClass);
    } catch (Exception ex) {
      fail("Training classifier failed: " + ex);

  public void testNumericClassSwapNominalValuesReorderAtts() {
    performTest(false, 4, 3, true, true, false);
  }
  
  protected InputMappedClassifier trainClassifier(Instances data, boolean nominalClass) {
    InputMappedClassifier toUse = new InputMappedClassifier();
    if (nominalClass) {
      toUse.setClassifier(new weka.classifiers.trees.J48());
    } else {
      toUse.setClassifier(new weka.classifiers.functions.LinearRegression());
    }
    toUse.setSuppressMappingReport(true);
    
    try {
      toUse.buildClassifier(data);
    } catch (Exception ex) {
      fail("Training InputMappedClassifier failed: " + ex);
      return null;
    }

Examples of weka.classifiers.misc.InputMappedClassifier

Related Classes of weka.classifiers.misc.InputMappedClassifier