与两种基于免疫原理的文本分类方法和传统的贝叶斯分类器进行了比较研究。
It is compared with two kinds of classifier, which is based on the principle of immunity, and traditional Bayesian classification.
传统的乐器识别方法采用的是树型分类方法，这种方法分类过程比较繁琐，而且精度不高。
The traditional instrument recognition method adopts binary-tree classifying method. The process of this method is trivial and inaccurate.
经实验证明，用该方法构造的决策树与传统的基于信息熵方法构造的决策树相比较，复杂性低，且能有效提高分类效果。
The experiments show that, compared with the entropy-based method, our method is simpler in the structure, and can improve the efficiency of classification.
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