本文提出一种综合粗糙集与支持向量机的 Web 文本分类模型，利用粗糙集的属性约简方法，减少支持向量机训练数据的维数，提高 Web 文本分类的性能与效率.-This article advances a Web text classification model which synthesis rough set and support vector machine. Using the rough set’s attribute reduction method to reduce the di

A simple method of data classification using rough set theory is described, as implemented by the tools in Alexander Ohra s software application ROSETTA

关键词:文本分类 特征降维 规则抽取 模式聚合 粗糙集 -Keywords: text classification feature dimension reduction rule extraction model aggregation rough set