基于发现特征子空间模型的文本分类算法*

在非结构化数据挖掘结构模型，即发现特征子空间模型(DFSSM)的运行机制下，提出了一种新的文本分类算法——基于DFSSM 的文本分类(TCDFSSM) 算法。该算法在文本训练及分类阶段的基础上增加了自动反馈阶段，使得TCDFSSM具有自学习能力，并给出了文本分类过程反馈阈值的选取算法。结果表明，该算法分类效果良好，其自学习能力、适应性及鲁棒性更加优越。

Text classification algorithm based on discovery feature sub-space model

Under the background of the nonstructural data mining model,this paper proposed a text classification algorithm based on the discovery feature sub-space model (DFSSM), TCDFSSM algorithm.The algorithm used an automatic feedback stage based on the text of the training and classification stage, making it self-learning ability. And it also provided the selection method of the feedback threshold in the text classification process. Experiments show that this algorithm works well, its self-learning ability, adaptability and robustness more superior.