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

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.

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.