关键词: 函数型数据, 特征选择, 互信息, 动态互信息, 动态条件互信息

Abstract: Functional data are concerned with the observed data as a whole, and focus on the intrinsic structure rather than the presentation form of the data. Compared with the traditional data, functional data contain more information, so the analysis and research on functional data have great value. In functional data analysis, feature selection is also an important issue. This paper proposes the dynamic mutual information (DMI) feature selection method for functional data by sorting features and selecting features dynamically by applying the mutual information theory, which takes account of the intrinsic data features. A stable subset of features can not only be obtained, but also the role of samples in feature selection is fully considered. Thus, the redundancy of information can be avoided. Besides, this paper proposes the dynamic conditional mutual information (DCMI) feature selection method by considering the influence of selected features on candidate features in dynamical feature selection process. The measure of the impact is based on conditional mutual information theory, and the relationship between features and feature subset can be descripted more appropriately. The experimental results on the UCR datasets show that the proposed DMI and DCMI can achieve small feature subset and good classification accuracy.

Key words: functional data, feature selection, mutual information, dynamic mutual information (DMI), dynamic conditional mutual information (DCMI)