@inproceedings{ed7392e250eb437b96643f6cf3b9d493,
title = "S-shaped vs. V-shaped transfer functions for ant lion optimization algorithm in feature selection problem",
abstract = "Feature selection is an important preprocessing step for classification problems. It deals with selecting near optimal features in the original dataset. Feature selection is an NP-hard problem, so meta-heuristics can be more efficient than exact methods. In this work, Ant Lion Optimizer (ALO), which is a recent metaheuristic algorithm, is employed as a wrapper feature selection method. Six variants of ALO are proposed where each employ a transfer function to map a continuous search space to a discrete search space. The performance of the proposed approaches is tested on eighteen UCI datasets and compared to a number of existing approaches in the literature: Particle Swarm Optimization, Gravitational Search Algorithm and two existing ALO-based approaches. Computational experiments show that the proposed approaches efficiently explore the feature space and select the most informative features, which help to improve the classification accuracy.",
keywords = "Antlion optimization algorithm, Classification, Feature selection, Optimization, Transfer functions",
author = "Majdi Mafarja and Derar Eleyan and Salwani Abdullah and Seyedali Mirjalili",
year = "2017",
month = jul,
day = "19",
doi = "10.1145/3102304.3102325",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
booktitle = "Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017",
note = "2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 ; Conference date: 19-07-2017 Through 20-07-2017",
}