通过对训练数据的学习，生成用于轨道故障判决的决策树(或者规则)。
The decision tree (or rules) used for rail deformation detection was generated by learning the train data.
你的分析重点是上下文表示方法和训练数据的特征对生成的类的质量的影响。
Your analysis will focus on the impact of context representation and the features of training data on the quality of generated clusters.
提出了关键技术， 包括：挖掘主题的定义方法、海量训练样本的在线生成和高性能数据挖掘算法。
The key technologies is proposed, including methods of definition of mining topics, online acquirement of extra large amount of training samples, and algorithms of data mining with high performance.
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