分析了常用的几种特征选取方法，提出了改进互信息算法。
Several feature selection methods were analyzed. An improved mutual information algorithm was proposed.
分析了常用的几种特征选取方法，提出了改进互信息算法。实验结果显示改进的互信息算法是可行的。
Several feature selection methods were analyzed. An improved mutual information algorithm was proposed. The experiment results showed that improved mutual information algorithm was feasible.
特征选择的方法上，结合了文档频数和互信息量，并对他们进行了改进。
On feature selection, document frequency was combined with mutual information, and performance was improved.
实验证明，本文提出的改进互信息配准方法更加稳定，且能获得更高的配准精度。
Experiments showed that the proposed method is more stable than the conventional method and is capable of getting higher accuracy.
实验证明，本文提出的改进互信息配准方法更加稳定，且能获得更高的配准精度。
Experiments showed that the proposed method is more stable than the conventional method and is capable of getting higher accuracy.
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