test_class.file: src/classify/SoftmaxClassifierTest.java
test_class.identifier: SoftmaxClassifierTest
test_case.body: @Test
  	public void dummyMultiClassTest (){
  		int numItems = 400;
  		String dir = "data/parsed";
  		DataSet<LabeledDatum<Double, Integer>,Double> Dataset 
  		= new DataSet<LabeledDatum<Double, Integer>,Double>(numItems);
  
  		int l = 0;
  		double[] x = new double[2];
  		
  		try {
  			FileInputStream fstream = new FileInputStream(dir + "/fournary_test.txt");
  			DataInputStream in = new DataInputStream(fstream);
  			BufferedReader br = new BufferedReader(new InputStreamReader(in));
  
  			for (int i = 0; i < numItems; i++) {
  				String[] parts = br.readLine().split(" ");
  				x[0] = Double.parseDouble(parts[0]);
  				x[1] = Double.parseDouble(parts[1]);
  				l = Integer.parseInt(parts[2]);
  
  				Dataset.add(new ReviewFeatures(l + " ", l, i, x));
  			}
  
  			fstream.close();
  			in.close();
  			br.close();
  		} catch (Exception e) {
  			System.err.println(e.getMessage());
  		}
  		
  		SoftmaxClassifier<Double, Integer> c = new SoftmaxClassifier<Double, Integer>( );
  
  		for(int i=0; i<10; i++)
  		{
  			Accuracy a = c.train(Dataset.Data);
  			System.out.println(a);
  			assertTrue( a.Accuracy == 1.0 );
  		}
  	}
test_case.class_method_signature: SoftmaxClassifierTest.dummyMultiClassTest()
test_case.full_signature: @Test public void dummyMultiClassTest()
test_case.identifier: dummyMultiClassTest
test_case.invocations: split readLine parseDouble parseDouble parseInt add close close close println getMessage train println assertTrue
test_case.modifiers: @Test public
test_case.parameters: ()
test_case.return: void
test_case.signature: void dummyMultiClassTest()
focal_class.declarator: serialVersionUID = 3043693828283322518L
focal_class.modifier: private static final
focal_class.original_string: private static final long serialVersionUID = 3043693828283322518L;
focal_class.type: long
focal_class.var_name: serialVersionUID
focal_class.declarator: MaxIterations = 100
focal_class.modifier: private final
focal_class.original_string: private final int MaxIterations = 100;
focal_class.type: int
focal_class.var_name: MaxIterations
focal_class.declarator: Lambda = 1e-6
focal_class.modifier: private final
focal_class.original_string: private final double Lambda = 1e-6;
focal_class.type: double
focal_class.var_name: Lambda
focal_class.declarator: LabelSet
focal_class.modifier: private
focal_class.original_string: private Counter<L> LabelSet;
focal_class.type: Counter<L>
focal_class.var_name: LabelSet
focal_class.declarator: trainScores
focal_class.modifier: private
focal_class.original_string: private DoubleMatrix trainScores, testScores;
focal_class.type: DoubleMatrix
focal_class.var_name: trainScores
focal_class.declarator: CostFunction
focal_class.modifier: private
focal_class.original_string: private SoftmaxCost CostFunction;
focal_class.type: SoftmaxCost
focal_class.var_name: CostFunction
focal_class.declarator: CatSize
focal_class.original_string: int CatSize;
focal_class.type: int
focal_class.var_name: CatSize
focal_class.declarator: ClassifierTheta
focal_class.original_string: ClassifierTheta ClassifierTheta;
focal_class.type: ClassifierTheta
focal_class.var_name: ClassifierTheta
focal_class.declarator: minFunc
focal_class.original_string: Minimizer<DifferentiableFunction> minFunc;
focal_class.type: Minimizer<DifferentiableFunction>
focal_class.var_name: minFunc
focal_class.declarator: TrainAccuracy
focal_class.original_string: Accuracy TrainAccuracy, TestAccuracy;
focal_class.type: Accuracy
focal_class.var_name: TrainAccuracy
focal_class.file: src/classify/SoftmaxClassifier.java
focal_class.identifier: SoftmaxClassifier
focal_class.interfaces: implements ProbabilisticClassifier<F,L>, Serializable
focal_class.class_method_signature: SoftmaxClassifier.SoftmaxClassifier( )
focal_class.full_signature: public  SoftmaxClassifier( )
focal_class.identifier: SoftmaxClassifier
focal_class.modifiers: public
focal_class.parameters: ( )
focal_class.signature:  SoftmaxClassifier( )
focal_class.class_method_signature: SoftmaxClassifier.SoftmaxClassifier(ClassifierTheta ClassifierParams, Set<L> labelSet)
focal_class.full_signature: public  SoftmaxClassifier(ClassifierTheta ClassifierParams, Set<L> labelSet)
focal_class.identifier: SoftmaxClassifier
focal_class.modifiers: public
focal_class.parameters: (ClassifierTheta ClassifierParams, Set<L> labelSet)
focal_class.signature:  SoftmaxClassifier(ClassifierTheta ClassifierParams, Set<L> labelSet)
focal_class.class_method_signature: SoftmaxClassifier.getTrainingResults(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: public DoubleMatrix getTrainingResults(List<LabeledDatum<F,L>> Data)
focal_class.identifier: getTrainingResults
focal_class.modifiers: public
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: DoubleMatrix
focal_class.signature: DoubleMatrix getTrainingResults(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.train(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: public Accuracy train(List<LabeledDatum<F,L>> Data)
focal_class.identifier: train
focal_class.modifiers: public
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: Accuracy
focal_class.signature: Accuracy train(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.test(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: public Accuracy test(List<LabeledDatum<F,L>> Data)
focal_class.identifier: test
focal_class.modifiers: public
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: Accuracy
focal_class.signature: Accuracy test(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.getTrainScores()
focal_class.full_signature: public DoubleMatrix getTrainScores()
focal_class.identifier: getTrainScores
focal_class.modifiers: public
focal_class.parameters: ()
focal_class.return: DoubleMatrix
focal_class.signature: DoubleMatrix getTrainScores()
focal_class.class_method_signature: SoftmaxClassifier.getTestScores()
focal_class.full_signature: public DoubleMatrix getTestScores()
focal_class.identifier: getTestScores
focal_class.modifiers: public
focal_class.parameters: ()
focal_class.return: DoubleMatrix
focal_class.signature: DoubleMatrix getTestScores()
focal_class.class_method_signature: SoftmaxClassifier.populateLabels(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: private void populateLabels(List<LabeledDatum<F,L>> Data)
focal_class.identifier: populateLabels
focal_class.modifiers: private
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: void
focal_class.signature: void populateLabels(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.makeLabelVector(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: private int[] makeLabelVector(List<LabeledDatum<F,L>> Data)
focal_class.identifier: makeLabelVector
focal_class.modifiers: private
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: int[]
focal_class.signature: int[] makeLabelVector(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.makeFeatureMatrix(List<LabeledDatum<F,L>> Data)
focal_class.full_signature: private DoubleMatrix makeFeatureMatrix(List<LabeledDatum<F,L>> Data)
focal_class.identifier: makeFeatureMatrix
focal_class.modifiers: private
focal_class.parameters: (List<LabeledDatum<F,L>> Data)
focal_class.return: DoubleMatrix
focal_class.signature: DoubleMatrix makeFeatureMatrix(List<LabeledDatum<F,L>> Data)
focal_class.class_method_signature: SoftmaxClassifier.getLabel(Datum<F> datum)
focal_class.full_signature: @Override public L getLabel(Datum<F> datum)
focal_class.identifier: getLabel
focal_class.modifiers: @Override public
focal_class.parameters: (Datum<F> datum)
focal_class.return: L
focal_class.signature: L getLabel(Datum<F> datum)
focal_class.class_method_signature: SoftmaxClassifier.getProbabilities(Datum<F> datum)
focal_class.full_signature: @Override public Counter<L> getProbabilities(Datum<F> datum)
focal_class.identifier: getProbabilities
focal_class.modifiers: @Override public
focal_class.parameters: (Datum<F> datum)
focal_class.return: Counter<L>
focal_class.signature: Counter<L> getProbabilities(Datum<F> datum)
focal_class.class_method_signature: SoftmaxClassifier.getLogProbabilities(Datum<F> datum)
focal_class.full_signature: @Override public Counter<L> getLogProbabilities(Datum<F> datum)
focal_class.identifier: getLogProbabilities
focal_class.modifiers: @Override public
focal_class.parameters: (Datum<F> datum)
focal_class.return: Counter<L>
focal_class.signature: Counter<L> getLogProbabilities(Datum<F> datum)
focal_class.class_method_signature: SoftmaxClassifier.Dump(String fileName)
focal_class.full_signature: public void Dump(String fileName)
focal_class.identifier: Dump
focal_class.modifiers: public
focal_class.parameters: (String fileName)
focal_class.return: void
focal_class.signature: void Dump(String fileName)
focal_method.body: public Accuracy train(List<LabeledDatum<F,L>> Data)
  	{	
  		trainScores = getTrainingResults(Data);
  		int[] GTLabels = makeLabelVector(Data);
  		int[] Predictions = trainScores.columnArgmaxs();
  		TrainAccuracy = new Accuracy(Predictions, GTLabels, CatSize);
  		return TrainAccuracy;
  	}
focal_method.class_method_signature: SoftmaxClassifier.train(List<LabeledDatum<F,L>> Data)
focal_method.full_signature: public Accuracy train(List<LabeledDatum<F,L>> Data)
focal_method.identifier: train
focal_method.invocations: getTrainingResults makeLabelVector columnArgmaxs
focal_method.modifiers: public
focal_method.parameters: (List<LabeledDatum<F,L>> Data)
focal_method.return: Accuracy
focal_method.signature: Accuracy train(List<LabeledDatum<F,L>> Data)