code: public Classifier<L, F> trainClassifierSemiSup(GeneralDataset<L, F> data, GeneralDataset<L, F> biasedData, double[][] confusionMatrix, double[] initial) {
      double[][] weights =  trainWeightsSemiSup(data, biasedData, confusionMatrix, initial);
      LinearClassifier<L, F> classifier = new LinearClassifier<L, F>(weights, data.featureIndex(), data.labelIndex());
      return classifier;
    }
docs: IMPORTANT: dataset and biasedDataset must have same featureIndex, labelIndex