Classification by machine learning is an important technique to predict gene functions.

应用机器学习进行分类是基因功能预测的一种重要手段。

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There are eight features used to form the feature vector for each sentence, and the summarizer is gained by machine learning algorithms, so automatic summarization is changed into classification task.

用这些特征构成句子向量表示，并用机器学习的方法对其进行训练得到器，从而把自动文摘转换为分类问题。

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By using rough set theory, this paper structures classification rules and processes the support vector machine feedback results with learning the train set.

利用粗糙集理论，通过对训练集的学习，构造分类规则，对支持向量机反馈后的结果再次进行处理。

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