dist/multilabel/BinarySegmentation.js
function(sample, classes) {
		sample = this.sampleToFeatures(sample, this.featureExtractors);
		classes = hash.normalized(classes);
		for (var positiveClass in classes) {
			this.makeSureClassifierExists(positiveClass);
			this.mapClassnameToClassifier[positiveClass].trainOnline(sample, 1);
		}
		for (var negativeClass in this.mapClassnameToClassifier) {
			if (!classes[negativeClass])
				this.mapClassnameToClassifier[negativeClass].trainOnline(sample, 0);
		}
	}
function(sample, classes) {
		sample = this.sampleToFeatures(sample, this.featureExtractors);
		classes = hash.normalized(classes);
		for (var positiveClass in classes) {
			this.makeSureClassifierExists(positiveClass);
			this.mapClassnameToClassifier[positiveClass].trainOnline(sample, 1);
		}
		for (var negativeClass in this.mapClassnameToClassifier) {
			if (!classes[negativeClass])
				this.mapClassnameToClassifier[negativeClass].trainOnline(sample, 0);
		}
	}
/* Tell the classifier that the given sample belongs to the given classes.

@param sample
a document.
@param classes
an object whose KEYS are classes, or an array whose VALUES are classes.