Semi-supervised Feature Selection Algorithm Based on Extension of Label
基于类标号扩展的半监督特征选择算法

Feature selection is an important step during data mining and machine learning.With the lack of labeled instances,the problem of effective selection is worthy of consideration.This paper proposed a novel semi-supervised feature selection algorithm based on the definition of inter-set and intra-set correlation,which starts from the original and small labeled samples and gains the final clusters by extension of labels.A complex evaluation was utilized as criterion to find optimal feature subset.Finally,the ex...