List of buildClassifier() Examples

Examples of buildClassifier()

org.goai.classification.impl.WekaClassifier.buildClassifier()
Trains classifier with passed date set @param itemClassMap Map
weka.classifiers.Classifier.buildClassifier()
Generates a classifier. Must initialize all fields of the classifier that are not being set via options (ie. multiple calls of buildClassifier must always lead to the same result). Must not change the dataset in any way. @param data set of instances serving as training data @exception Exception if the classifier has not been generated successfully
weka.classifiers.bayes.BayesNet.buildClassifier()
Generates the classifier. @param instances set of instances serving as training data @throws Exception if the classifier has not been generatedsuccessfully
weka.classifiers.bayes.NaiveBayesUpdateable.buildClassifier()
weka.classifiers.functions.LibSVM.buildClassifier()
builds the classifier @param insts the training instances @throws Exception if libsvm classes not in classpath or libsvmencountered a problem
weka.classifiers.functions.LinearRegression.buildClassifier()
Builds a regression model for the given data. @param data the training data to be used for generating thelinear regression function @throws Exception if the classifier could not be built successfully
weka.classifiers.functions.MultilayerPerceptron.buildClassifier()
Call this function to build and train a neural network for the training data provided. @param i The training data. @throws Exception if can't build classification properly.
weka.classifiers.functions.SMO.buildClassifier()
Method for building the classifier. Implements a one-against-one wrapper for multi-class problems. @param insts the set of training instances @throws Exception if the classifier can't be built successfully
weka.classifiers.functions.SPegasos.buildClassifier()
Method for building the classifier. @param data the set of training instances. @throws Exception if the classifier can't be built successfully.
weka.classifiers.meta.FilteredClassifier.buildClassifier()
Build the classifier on the filtered data. @param data the training data @throws Exception if the classifier could not be built successfully
weka.classifiers.misc.InputMappedClassifier.buildClassifier()
Build the classifier @param data the training data to be used for generating thebagged classifier. @throws Exception if the classifier could not be built successfully
weka.classifiers.trees.J48.buildClassifier()
Generates the classifier. @param instances the data to train the classifier with @throws Exception if classifier can't be built successfully

Examples of weka.classifiers.functions.SMO.buildClassifier()

        // smo.setNormalizeData(numAttrLeft < 40);
        smo.setFilterType(new SelectedTag(m_smoFilterType, SMO.TAGS_FILTER));
        smo.setEpsilon(m_smoPParameter);
        smo.setToleranceParameter(m_smoTParameter);
        smo.setC(m_smoCParameter);
        smo.buildClassifier(trainCopy);
                                
        // Find the attribute with maximum weight^2
        double[] weightsSparse = smo.sparseWeights()[0][1];
        int[] indicesSparse = smo.sparseIndices()[0][1];
        double[] weights = new double[trainCopy.numAttributes()];

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Examples of weka.classifiers.functions.SPegasos.buildClassifier()

        Instances trainingSet = fillDataSet(trainingSamples, labels, numFeats);
        Instances initial = trainingSet.stringFreeStructure();
        Evaluation eTest = null;
        SPegasos cModel = new SPegasos();
        try {
            cModel.buildClassifier(initial);
            for (int i = 0; i < trainingSet.numInstances(); i++) {
                cModel.updateClassifier(trainingSet.instance(i));
            }
            eTest = new Evaluation(trainingSet);
            if (numFolds > trainingSet.numInstances()) {

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

        // filtered classifier
        FilteredClassifier fc = new FilteredClassifier();
        fc.setFilter(rm);
        fc.setClassifier(j48);
        // train using stock_training_data.arff:
        fc.buildClassifier(training_data);
        // test using stock_testing_data.arff:
        for (int i = 0; i < testing_data.numInstances(); i++) {
          double pred = fc.classifyInstance(testing_data.instance(i));
          System.out.print("given value: " + testing_data.classAttribute().value((int)testing_data.instance(i).classValue()));
          System.out.println(". predicted value: " + testing_data.classAttribute().value((int) pred));

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

        classifier_aset.add(cluster_attr);
        fc.setFilter(classifier_aset.createFilter(newData));
        fc.setClassifier(j48);
        
        // Bombs away!
        fc.buildClassifier(newData);
        
        return (fc);
    }

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

            FilteredClassifier filteredClassifier = new FilteredClassifier();
            filteredClassifier.setFilter(removeIDFilter);
            filteredClassifier.setClassifier(classifier);
               
            // Build the classifier
            filteredClassifier.buildClassifier(train);
             
            // Evaluate
            eval.evaluateModel(classifier, test);
            
            // Add predictions

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

          FilteredClassifier filteredClassifier = new FilteredClassifier();
          filteredClassifier.setFilter(removeIDFilter);
          filteredClassifier.setClassifier(classifier);
             
          // Build the classifier
          filteredClassifier.buildClassifier(train);
           
          // Evaluate
          eval.evaluateModel(filteredClassifier, test);
          
          // Add predictions

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

            FilteredClassifier filteredClassifier = new FilteredClassifier();
            filteredClassifier.setFilter(removeIDFilter);
            filteredClassifier.setClassifier(classifier);
               
            // Build the classifier
            filteredClassifier.buildClassifier(train);
             
            // Evaluate
            eval.evaluateModel(classifier, test);
            
            // Add predictions

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

        FilteredClassifier filteredClassifier = new FilteredClassifier();
        filteredClassifier.setFilter(removeIDFilter);
        filteredClassifier.setClassifier(classifier);
           
        // Build the classifier
        filteredClassifier.buildClassifier(train);
    
        // Prepare the output buffer 
        AbstractOutput output = new PlainText();
        output.setBuffer(new StringBuffer());
        output.setHeader(test);

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

          FilteredClassifier filteredClassifier = new FilteredClassifier();
          filteredClassifier.setFilter(removeIDFilter);
          filteredClassifier.setClassifier(classifier);
             
          // Build the classifier
          filteredClassifier.buildClassifier(train);
          
          // Evaluate
          eval.evaluateModel(filteredClassifier, test);
          
          // Add predictions

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Examples of weka.classifiers.meta.FilteredClassifier.buildClassifier()

  classifier.setClassifier(new ZeroR());
      }
      classifier.setFilter(filter);
      
      if (!m_classifiers.containsKey(node.m_left.getString() + "|" + node.m_right.getString())) {
  classifier.buildClassifier(data);
  m_classifiers.put(node.m_left.getString() + "|" + node.m_right.getString(), classifier);
      } else {
  classifier=(FilteredClassifier)m_classifiers.get(node.m_left.getString() + "|" + 
               node.m_right.getString());
      }

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