- Title
- An adaptive memetic algorithm for feature selection using proxity graphs
- Creator
- Abu Zaher, Amer; Berretta, Regina; Noman, Nasimul; Moscato, Pablo
- Relation
- Computational Intelligence Vol. 35, Issue 1, p. 156-183
- Publisher
- Wiley
- Resource Type
- journal article
- Date
- 2018
- Description
- We propose a multivariate feature selection method that uses proximity graphs for assessing the quality of feature subsets. Initially, a complete graph is built, where nodes are the samples, and edge weights are calculated considering only the selected features. Next, a proximity graph is constructed on the basis of these weights and different fitness functions, calculated over the proximity graph, to evaluate the quality of the selected feature set. We propose an iterative methodology on the basis of a memetic algorithm for exploring the space of possible feature subsets aimed at maximizing a quality score. We designed multiple local search strategies, and we used an adaptive strategy for automatic balancing between the global and local search components of the memetic algorithm. The computational experiments were carried out using four well‐known data sets. We investigate the suitability of three different proximity graphs (minimum spanning tree, k ‐nearest neighbors, and relative neighborhood graph) for the proposed approach. The selected features have been evaluated using a total of 49 classification methods from an open‐source data mining and machine learning package (WEKA). The computational results show that the proposed adaptive memetic algorithm can perform better than traditional genetic algorithms in finding more useful feature sets. Finally, we establish the competitiveness of our approach by comparing it with other well‐known feature selection methods..
- Subject
- evolutionary algorithm; feature selection; memetic algorithm; minimum spanning tree; proximity graph
- Identifier
- http://hdl.handle.net/1959.13/1414643
- Identifier
- uon:36788
- Identifier
- ISSN:1467-8640
- Rights
- This is the peer reviewed version of the following article: Abu Zeher, A., Berretta, R. and Noman, N. et al. (2019) An adaptive memetic algorithm for feature selection using proximity graphs, Computational Intelligence, 35(1) 156-183 which has been published in final form at: http://dx.doi.org/10.1111/coin.12196. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
- Language
- eng
- Full Text
- Reviewed
- Hits: 5154
- Visitors: 3049
- Downloads: 296
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Author final version | 1 MB | Adobe Acrobat PDF | View Details Download |