Examples of Bagging

org.apache.mahout.classifier.df.Bagging
Builds a tree using bagging
org.apache.mahout.df.Bagging
Builds a tree using bagging

weka.classifiers.meta.Bagging

Class for bagging a classifier to reduce variance. Can do classification and regression depending on the base learner.

For more information, see

Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.

BibTeX:

 @article{Breiman1996, author = {Leo Breiman}, journal = {Machine Learning}, number = {2}, pages = {123-140}, title = {Bagging predictors}, volume = {24}, year = {1996} }

Valid options are:

 -P Size of each bag, as a percentage of the training set size. (default 100)

 -O Calculate the out of bag error.

 -S <num> Random number seed. (default 1)

 -I <num> Number of iterations. (default 10)

 -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.trees.REPTree)

  Options specific to classifier weka.classifiers.trees.REPTree:

 -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)

Options after -- are passed to the designated classifier.

@author Eibe Frank (eibe@cs.waikato.ac.nz) @author Len Trigg (len@reeltwo.com) @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @version $Revision: 6502 $

Examples of org.apache.mahout.classifier.df.Bagging

  protected void cleanup(Context context) throws IOException, InterruptedException {
    // prepare the data
    log.debug("partition: {} numInstances: {}", partition, instances.size());
    
    Data data = new Data(getDataset(), instances);
    Bagging bagging = new Bagging(getTreeBuilder(), data);
    
    TreeID key = new TreeID();
    
    log.debug("Building {} trees", nbTrees);
    for (int treeId = 0; treeId < nbTrees; treeId++) {
      log.debug("Building tree number : {}", treeId);
      
      Node tree = bagging.build(rng);
      
      key.set(partition, firstTreeId + treeId);
      
      if (isOutput()) {
        MapredOutput emOut = new MapredOutput(tree);

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Examples of org.apache.mahout.classifier.df.Bagging

    
    log.info("Loading the data...");
    Data data = loadData(conf, getDataset());
    log.info("Data loaded : {} instances", data.size());
    
    bagging = new Bagging(getTreeBuilder(), data);
  }

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Examples of org.apache.mahout.classifier.df.Bagging

   * @param data
   *          training data
   */
  public SequentialBuilder(Random rng, TreeBuilder treeBuilder, Data data) {
    this.rng = rng;
    bagging = new Bagging(treeBuilder, data);
  }

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Examples of org.apache.mahout.classifier.df.Bagging

  protected void cleanup(Context context) throws IOException, InterruptedException {
    // prepare the data
    log.debug("partition: {} numInstances: {}", partition, instances.size());
    
    Data data = new Data(getDataset(), instances);
    Bagging bagging = new Bagging(getTreeBuilder(), data);
    
    TreeID key = new TreeID();
    
    log.debug("Building {} trees", nbTrees);
    for (int treeId = 0; treeId < nbTrees; treeId++) {
      log.debug("Building tree number : {}", treeId);
      
      Node tree = bagging.build(rng);
      
      key.set(partition, firstTreeId + treeId);
      
      if (isOutput()) {
        MapredOutput emOut = new MapredOutput(tree);

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Examples of org.apache.mahout.classifier.df.Bagging

  protected void cleanup(Context context) throws IOException, InterruptedException {
    // prepare the data
    log.debug("partition: {} numInstances: {}", partition, instances.size());
    
    Data data = new Data(getDataset(), instances);
    Bagging bagging = new Bagging(getTreeBuilder(), data);
    
    TreeID key = new TreeID();
    
    log.debug("Building {} trees", nbTrees);
    for (int treeId = 0; treeId < nbTrees; treeId++) {
      log.debug("Building tree number : {}", treeId);
      
      Node tree = bagging.build(rng);
      
      key.set(partition, firstTreeId + treeId);
      
      if (!isNoOutput()) {
        MapredOutput emOut = new MapredOutput(tree);

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Examples of org.apache.mahout.classifier.df.Bagging

    
    log.info("Loading the data...");
    Data data = loadData(conf, getDataset());
    log.info("Data loaded : {} instances", data.size());
    
    bagging = new Bagging(getTreeBuilder(), data);
  }

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Examples of org.apache.mahout.classifier.df.Bagging

  protected void cleanup(Context context) throws IOException, InterruptedException {
    // prepare the data
    log.debug("partition: {} numInstances: {}", partition, instances.size());
    
    Data data = new Data(getDataset(), instances);
    Bagging bagging = new Bagging(getTreeBuilder(), data);
    
    TreeID key = new TreeID();
    
    log.debug("Building {} trees", nbTrees);
    for (int treeId = 0; treeId < nbTrees; treeId++) {
      log.debug("Building tree number : {}", treeId);
      
      Node tree = bagging.build(rng);
      
      key.set(partition, firstTreeId + treeId);
      
      if (isOutput()) {
        MapredOutput emOut = new MapredOutput(tree);

View Full Code Here

Examples of org.apache.mahout.df.Bagging

  protected void cleanup(Context context) throws IOException, InterruptedException {
    // prepare the data
    log.debug("partition: {} numInstances: {}", partition, instances.size());
    
    Data data = new Data(getDataset(), instances);
    Bagging bagging = new Bagging(getTreeBuilder(), data);
    
    TreeID key = new TreeID();
    
    log.debug("Building {} trees", nbTrees);
    SingleTreePredictions callback = null;
    int[] predictions = null;
    for (int treeId = 0; treeId < nbTrees; treeId++) {
      log.debug("Building tree number : {}", treeId);
      if (isOobEstimate() && !isNoOutput()) {
        callback = new SingleTreePredictions(data.size());
        predictions = callback.getPredictions();
      }
      
      Node tree = bagging.build(treeId, rng, callback);
      
      key.set(partition, firstTreeId + treeId);
      
      if (!isNoOutput()) {
        MapredOutput emOut = new MapredOutput(tree, predictions);

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Examples of org.apache.mahout.df.Bagging

   * @param data
   *          training data
   */
  public SequentialBuilder(Random rng, TreeBuilder treeBuilder, Data data) {
    this.rng = rng;
    bagging = new Bagging(treeBuilder, data);
  }

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Examples of org.apache.mahout.df.Bagging

    
    log.info("Loading the data...");
    data = loadData(conf, getDataset());
    log.info("Data loaded : {} instances", data.size());
    
    bagging = new Bagging(getTreeBuilder(), data);
  }

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