import cc.mallet.fst.CRFTrainerByStochasticGradient; //导入依赖的package包/类
public void testTrainStochasticGradient() {
	Pipe p = makeSpacePredictionPipe();
	Pipe p2 = new TestCRF2String();

	InstanceList instances = new InstanceList(p);
	instances.addThruPipe(new ArrayIterator(data));
	InstanceList[] lists = instances.split(new double[] { .5, .5 });
	CRF crf = new CRF(p, p2);
	crf.addFullyConnectedStatesForLabels();
	crf.setWeightsDimensionAsIn(lists[0], false);
	CRFTrainerByStochasticGradient crft = new CRFTrainerByStochasticGradient(
			crf, 0.0001);
	System.out.println("Training Accuracy before training = "
			+ crf.averageTokenAccuracy(lists[0]));
	System.out.println("Testing  Accuracy before training = "
			+ crf.averageTokenAccuracy(lists[1]));
	System.out.println("Training...");
	// either fixed learning rate or selected on a sample
	crft.setLearningRateByLikelihood(lists[0]);
	// crft.setLearningRate(0.01);
	crft.train(lists[0], 100);
	crf.print();
	System.out.println("Training Accuracy after training = "
			+ crf.averageTokenAccuracy(lists[0]));
	System.out.println("Testing  Accuracy after training = "
			+ crf.averageTokenAccuracy(lists[1]));
}