贝叶斯并行分类分析

1 贝叶斯训练器

所在包：Package org.apache.mahout.classifier.bayes

实现机制

The implementation is divided up into three parts:

1. The Trainer -- responsible for doing the counting of the words and the labels

2. The Model -- responsible for holding the training data in a useful way

3. The Classifier -- responsible for using the trainers output to determine the category of previously unseen documents

1 训练器

The trainer is manifested in several classes:

1. BayesDriver

   创建 Hadoop 贝叶斯作业，输出模型，这个类封装了 4 个 map/reduce 类。

2. common.BayesFeatureDriver

3. common.BayesTfIdfDriver

4. common.BayesWeightSummerDriver

5. BayesThetaNormalizerDriver

训练器的输入是KeyValueTextInputFormat 格式，第一个字符时类标签，剩余的是特征（单词），如下面的格式：

hockey puck stick goalie forward defenseman referee ice checking slapshot helmet

 football field football pigskin referee helmet turf tackle
 

hockey 和football 是类标签，剩下的是特征。

2 模型