一种基于数据偏斜的改进KNN文本分类
An Improved KNN Text Categorization Method Based on Data Uneven
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摘要: KNN是一种简单、有效、非参数的分类算法.针对样本分布偏斜的分类环境, 首先提出了一种改进的特征选择方法进行特征降维, 在此基础上进一步提出了一种基于分布的改进KNN方法用于文本分类, 降低了分布偏斜问题对决策函数的影响.试验表明, 所提出的改进KNN文本分类方法具有较好的分类性能.Abstract: KNN is a simple, valid and non-parameter method often applied in categorization.Under the condition that the samples distribution is uneven, we first put forward an improved weighting way in feature reduction;then we improve the KNN basing on density in automatic text categorization.This way reduces the impact from the uneven distribution.we have a test about text categorization.The result shows that these methods have a better precision than the common KNN;similarity