高维特征集选择模型研究

Study on the model of feature selection from huge feature sets

特征选择是机器学习和模式识别等领域一个关键问题,而高维特征选择又是当今研究的热点和难点。从高维特征选择的模型出发,详细说明高维特征选择所采用的各种算法类型,并分析了该模型的优劣。

Feature selection is a key problem in machine learning and pattern recognition, at the same time, feature selection from huge sets(FSHS) is a hot and difficult subject for researchers to study. In this paper, through the model of FSHS, the authors categorize algorithms about FSHS, and analyze the advantages and disadvantages of the model.