分类(也即分类树或决策树)是一种数据挖掘算法，为如何确定一个新的数据实例的输出创建逐步指导。
Classification (also known as classification trees or decision trees) is a data mining algorithm that creates a step-by-step guide for how to determine the output of a new data instance.
在使用Classification Workbench之前，要收集预先分类的样本数据(例如文档)，这些数据应该反映将用ICM进行分类的数据的典型情况。
Prior to using Classification Workbench, you'll collect pre-categorized sample data (for example, documents) representative of the data you expect to classify using ICM.
为了解决该方法存在的训练数据集问题，本文改进了现有的贝叶斯分类算法，提出了利用未标记数据提高贝叶斯分类器性能的方法。
In order to solve the problem existing in training data sets, present Bayes algorithm is im - proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.
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