【摘要】 为了避免连续数据离散化处理时造成的信息损失,降低样本属性邻域求解的复杂度,提高特征基因提取的效率。该文在单调度量空间上,提出了一种基于单调邻域粗糙集的特征基因提取方法。并在两个标准的基因表达数据上进行了实验,结果证明该方法是有效可行的。更多还原

【Abstract】 In order to avoid the information losing when dispersing serial data,Lower complexity of sample attribute solving neighborhood,improve the efficiency of extracting characteristics gene.In this paper,on the monotonicity metric space,proposes a gene extraction method based on montonicity neighborhood rough set.And experiments it on the two standard gene expression data,the result proves that the method is effective and feasible.更多还原