Examples of org.apache.mahout.classifier.sgd.CrossFoldLearner

Package org.apache.mahout.classifier.sgd

Examples of org.apache.mahout.classifier.sgd.CrossFoldLearner

org.apache.mahout.classifier.sgd.CrossFoldLearner
Does cross-fold validation of log-likelihood and AUC on several online logistic regression models. Each record is passed to all but one of the models for training and to the remaining model for evaluation. In order to maintain proper segregation between the different folds across training data iterations, data should either be passed to this learner in the same order each time the training data is traversed or a tracking key such as the file offset of the training record should be passed with each training example.


      double lambda = 0;
      double mu = 0;


      if (best != null) {
        CrossFoldLearner state = best.getPayload().getLearner();
        averageCorrect = state.percentCorrect();
        averageLL = state.logLikelihood();


        OnlineLogisticRegression model = state.getModels().get(0);
        // finish off pending regularization
        model.close();
        
        Matrix beta = model.getBeta();
        maxBeta = beta.aggregate(Functions.MAX, Functions.ABS);

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  }


  private static void dissect(Dictionary newsGroups,
                              AdaptiveLogisticRegression learningAlgorithm,
                              Iterable<File> files) throws IOException {
    CrossFoldLearner model = learningAlgorithm.getBest().getPayload().getLearner();
    model.close();


    Map<String, Set<Integer>> traceDictionary = Maps.newTreeMap();
    ModelDissector md = new ModelDissector();


    encoder.setTraceDictionary(traceDictionary);

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org.apache.mahout.math.DenseVector

org.apache.mahout.math.function.BinaryFunction

org.apache.mahout.math.function.DoubleDoubleFunction

org.apache.mahout.math.Vector

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