import cc.mallet.types.FeatureInducer; //导入依赖的package包/类
/** This method is deprecated. */
// But it is here as a reminder to do something about induceFeaturesFor(). */
@Deprecated
public Sequence[] predict (InstanceList testing) {
	testing.setFeatureSelection(this.globalFeatureSelection);
	for (int i = 0; i < featureInducers.size(); i++) {
		FeatureInducer klfi = (FeatureInducer)featureInducers.get(i);
		klfi.induceFeaturesFor (testing, false, false);
	}
	Sequence[] ret = new Sequence[testing.size()];
	for (int i = 0; i < testing.size(); i++) {
		Instance instance = testing.get(i);
		Sequence input = (Sequence) instance.getData();
		Sequence trueOutput = (Sequence) instance.getTarget();
		assert (input.size() == trueOutput.size());
		Sequence predOutput = new MaxLatticeDefault(this, input).bestOutputSequence();
		assert (predOutput.size() == trueOutput.size());
		ret[i] = predOutput;
	}
	return ret;
}
 

import cc.mallet.types.FeatureInducer; //导入依赖的package包/类
@SuppressWarnings("unchecked")
 private void readObject (ObjectInputStream in) throws IOException, ClassNotFoundException {
	in.readInt ();
	inputAlphabet = (Alphabet) in.readObject ();
	outputAlphabet = (Alphabet) in.readObject ();
	states = (ArrayList<State>) in.readObject ();
	initialStates = (ArrayList<State>) in.readObject ();
	name2state = (HashMap) in.readObject ();
	parameters = (Factors) in.readObject ();
	globalFeatureSelection = (FeatureSelection) in.readObject ();		
	featureSelections = (FeatureSelection[]) in.readObject ();
	featureInducers = (ArrayList<FeatureInducer>) in.readObject ();
	weightsValueChangeStamp = in.readInt ();
	weightsStructureChangeStamp = in.readInt ();
	cachedNumParametersStamp = in.readInt ();
	numParameters = in.readInt ();
}
 

import cc.mallet.types.FeatureInducer; //导入依赖的package包/类
/** When the CRF has done feature induction, these new feature conjunctions must be 
 * created in the test or validation data in order for them to take effect. */
public void induceFeaturesFor (InstanceList instances) {
	instances.setFeatureSelection(this.globalFeatureSelection);
	for (int i = 0; i < featureInducers.size(); i++) {
		FeatureInducer klfi = featureInducers.get(i);
		klfi.induceFeaturesFor (instances, false, false);
	}
}