Java tutorial
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package com.netease.news.classifier.naivebayes; import org.apache.mahout.classifier.naivebayes.StandardNaiveBayesClassifier; import org.apache.mahout.math.Vector; public class StandardThetaTrainer extends AbstractThetaTrainer { public StandardThetaTrainer(Vector weightsPerFeature, Vector weightsPerLabel, double alphaI) { super(weightsPerFeature, weightsPerLabel, alphaI); } @Override public void train(int label, Vector perLabelWeight) { double labelWeight = labelWeight(label); for (Vector.Element e : perLabelWeight.nonZeroes()) { updatePerLabelThetaNormalizer(label, StandardNaiveBayesClassifier.computeWeight(e.get(), labelWeight, alphaI(), numFeatures())); } } }