public MaxEnt train (InstanceList trainingSet) { return train (trainingSet, numIterations); }
public MaxEnt train (InstanceList trainingSet) { return train (trainingSet, numIterations); }
public MaxEnt train (InstanceList trainingSet) { return train (trainingSet, numIterations); }
public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
/** Train underlying classifier on <code>ilist</code>. Assumes ilist has targst <code>correct</code> or <code>incorrect</code>. @param ilist training list to build correct/incorrect classifier @param correct "correct" label @param incorrect "incorrect" label */ public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
/** Train underlying classifier on <code>ilist</code>. Assumes ilist has targst <code>correct</code> or <code>incorrect</code>. @param ilist training list to build correct/incorrect classifier @param correct "correct" label @param incorrect "incorrect" label */ public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
/** Train underlying classifier on <code>ilist</code>. Assumes ilist has targst <code>correct</code> or <code>incorrect</code>. @param ilist training list to build correct/incorrect classifier @param correct "correct" label @param incorrect "incorrect" label */ public MaxEnt trainClassifier (InstanceList ilist, String correct, String incorrect) { this.meClassifier = (MaxEnt) meTrainer.train (ilist); this.pipe = ilist.getPipe (); this.correct = correct; this.incorrect = incorrect; InfoGain ig = new InfoGain (ilist); int igl = Math.min (30, ig.numLocations()); for (int i = 0; i < igl; i++) System.out.println ("InfoGain["+ig.getObjectAtRank(i)+"]="+ig.getValueAtRank(i)); return this.meClassifier; }
public void testTrainedMaximizable () { MaxEntTrainer trainer = new MaxEntTrainer(); Alphabet fd = dictOfSize (6); String[] classNames = new String[] {"class0", "class1"}; InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20); MaxEnt me = (MaxEnt)trainer.train(ilist); Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist, me); TestOptimizable.testValueAndGradientCurrentParameters (maxable); }
public void testTrainedMaximizable () { MaxEntTrainer trainer = new MaxEntTrainer(); Alphabet fd = dictOfSize (6); String[] classNames = new String[] {"class0", "class1"}; InstanceList ilist = new InstanceList (new Randoms(1), fd, classNames, 20); MaxEnt me = (MaxEnt)trainer.train(ilist); Optimizable.ByGradientValue maxable = trainer.getOptimizable (ilist, me); TestOptimizable.testValueAndGradientCurrentParameters (maxable); }
Classifier classifier = new MaxEntTrainer().train(trainingInstances); logger.info("InfoGain:\n"); new InfoGain(trainingInstances).printByRank(System.out);
trainList.addThruPipe(new ClusterSampleIterator(training, random, 0.5, 100)); System.err.println("Created " + trainList.size() + " instances."); Classifier me = new MaxEntTrainer().train(trainList); ClassifyingNeighborEvaluator eval = new ClassifyingNeighborEvaluator(me, "YES");
trainList.addThruPipe(new ClusterSampleIterator(training, random, 0.5, 100)); System.err.println("Created " + trainList.size() + " instances."); Classifier me = new MaxEntTrainer().train(trainList); ClassifyingNeighborEvaluator eval = new ClassifyingNeighborEvaluator(me, "YES");
trainList.addThruPipe(new ClusterSampleIterator(training, random, 0.5, 100)); System.err.println("Created " + trainList.size() + " instances."); Classifier me = new MaxEntTrainer().train(trainList); ClassifyingNeighborEvaluator eval = new ClassifyingNeighborEvaluator(me, "YES");
Classifier cpc = confidencePredictingClassifierTrainer.train (confidencePredictionTraining); logger.info("Accuracy at predicting correct/incorrect in training = " + cpc.getAccuracy(confidencePredictionTraining));
Classifier cpc = confidencePredictingClassifierTrainer.train (confidencePredictionTraining); logger.info("Accuracy at predicting correct/incorrect in training = " + cpc.getAccuracy(confidencePredictionTraining));
Classifier cpc = confidencePredictingClassifierTrainer.train (confidencePredictionTraining); logger.info("Accuracy at predicting correct/incorrect in training = " + cpc.getAccuracy(confidencePredictionTraining));