NaiveBayes c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet); double prevLogLikelihood = 0, logLikelihood = 0; boolean converged = false; c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet2); logLikelihood = c.dataLogLikelihood (trainingSet2); System.err.println ("Loglikelihood = "+logLikelihood);
NaiveBayes c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet); double prevLogLikelihood = 0, logLikelihood = 0; boolean converged = false; c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet2); logLikelihood = c.dataLogLikelihood (trainingSet2); System.err.println ("Loglikelihood = "+logLikelihood);
NaiveBayes c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet); double prevLogLikelihood = 0, logLikelihood = 0; boolean converged = false; c = (NaiveBayes) nbTrainer.newClassifierTrainer().train (trainingSet2); logLikelihood = c.dataLogLikelihood (trainingSet2); System.err.println ("Loglikelihood = "+logLikelihood);
public void setPriorMultinomialEstimator (Multinomial.Estimator me) { priorEstimator = me; nbTrainer.setPriorMultinomialEstimator(priorEstimator); }
public void setPriorMultinomialEstimator (Multinomial.Estimator me) { priorEstimator = me; nbTrainer.setPriorMultinomialEstimator(priorEstimator); }
public void setDocLengthNormalization (double d) { docLengthNormalization = d; nbTrainer.setDocLengthNormalization(docLengthNormalization); }
public void setFeatureMultinomialEstimator (Multinomial.Estimator me) { featureEstimator = me; nbTrainer.setFeatureMultinomialEstimator(featureEstimator); }
public void setFeatureMultinomialEstimator (Multinomial.Estimator me) { featureEstimator = me; nbTrainer.setFeatureMultinomialEstimator(featureEstimator); }
public void setDocLengthNormalization (double d) { docLengthNormalization = d; nbTrainer.setDocLengthNormalization(docLengthNormalization); }
public void setDocLengthNormalization (double d) { docLengthNormalization = d; nbTrainer.setDocLengthNormalization(docLengthNormalization); }
public NaiveBayesEMTrainer () { nbTrainer = new NaiveBayesTrainer.Factory (); nbTrainer.setDocLengthNormalization(docLengthNormalization); nbTrainer.setFeatureMultinomialEstimator(featureEstimator); nbTrainer.setPriorMultinomialEstimator (priorEstimator); }
public void setPriorMultinomialEstimator (Multinomial.Estimator me) { priorEstimator = me; nbTrainer.setPriorMultinomialEstimator(priorEstimator); }
public void setFeatureMultinomialEstimator (Multinomial.Estimator me) { featureEstimator = me; nbTrainer.setFeatureMultinomialEstimator(featureEstimator); }
public NaiveBayesEMTrainer () { nbTrainer = new NaiveBayesTrainer.Factory (); nbTrainer.setDocLengthNormalization(docLengthNormalization); nbTrainer.setFeatureMultinomialEstimator(featureEstimator); nbTrainer.setPriorMultinomialEstimator (priorEstimator); }
public NaiveBayesEMTrainer () { nbTrainer = new NaiveBayesTrainer.Factory (); nbTrainer.setDocLengthNormalization(docLengthNormalization); nbTrainer.setFeatureMultinomialEstimator(featureEstimator); nbTrainer.setPriorMultinomialEstimator (priorEstimator); }