基于混合克隆量子遗传策略的文本特征选择方法

摘要

The metrics of vector reduction rate and classification accuracy, and to use of the qubits encoded on the genetic algorithm, combined with the cloning operator, this paper proposed a strategy based on hybrid genetic quantum cloning text feature selection method. Experimental results show that the method can effectively reduce the dimension of feature vector text, set of extracted features can improve the quantum accuracy of text classification.%引入向量约简率和分类准确率的度量标准,采用量子比特对遗传算法进行编码,结合克隆算子,提出一种基于混合克隆量子遗传策略的文本特征选择方法.实验结果显示,该方法能有效地降低文本特征向量的维度,所提取的特征向量子集能有效提高文本分类的精度.