A software for feature selection using single/multi-objective evolutionary algorithms
Main Page: https://github.com/Jiaweihuang/ECoFFeS
Current release: Version 1.0 (2017-2-12)
The recent decade has witnessed significant progress in the development of feature selection for many bioinformatics and cheminformatics applications, such as sequence analysis, microarray analysis, mass spectra (MS) analysis, single nucleotide polymorphism (SNP) analysis, and quantitative structure-activity relationship (QSAR) analysis. Compared with other dimensionality reduction techniques, feature selection merely selects a feature subset and does not alter the original representation of the features. Thus, the selected feature subset preserves the semantics of the features while offering the advantage of interpretability. For example, in QSAR analysis, the selected feature subset improves the interpretability of relationship between descriptors and biological activities.
However, feature selection remains a challenging task due to the fact that it is an NP-hard problem, in which the total number of possible feature subsets is 2^n-1 (n is the number of features). To deal with this issue, many methods have been proposed, such as complete search, greedy search, and heuristic search. Nevertheless, most of them tend to suffer from stagnation in a local optimum. Evolutionary computation, as a kind of powerful global search method inspired by nature, has attracted a high level of interest from the feature selection research community. For the purpose of further boosting evolutionary computation for feature selection, we have developed a user-friendly and standalone software named ECoFFeS (Evolutionary Computation For Feature Selection).
Subset Discovery is a search procedure to generate candidate feature subsets. ECoFFeS involves two novel EAs (modified DE and modified MOEA/D proposed by the authors) and four existing state-of-the-art EAs, namely, ACO, GA, PSO, and NSGA-II.
Subset Evaluation seeks to assess the candidate feature subsets generated by Subset Discovery. In ECoFFeS, 36 evaluation combinations are provided for users.
- Jiawei Huang, Yong Wang, Alex F Chen, Shengxiang Yang and Dongsheng Cao. ECoFFeS: a software for feature selection using single/multi-objective evolutionary algorithms. In submission