A Survey on Evolutionary Computation Approaches to Feature Selection
Bing Xue, Mengjie Zhang, Will N. Browne, Xin Yao
Feature selection is an important task in data mining and machine learning to reduce the dimensionality of the data and increase the performance of an algorithm, such as a classification algorithm. However, feature selection is a challenging task due mainly to the large search space. A variety of methods have been applied to solve feature selection problems, where evolutionary computation (EC) techniques have recently gained much attention and shown some success. However, there are no comprehensive guidelines on the strengths and weaknesses of alternative approaches. This leads to a disjointed and fragmented field with ultimately lost opportunities for improving performance and successful applications. This paper presents a comprehensive survey of the state-of-the-art work on EC for feature selection, which identifies the contributions of these different algorithms. In addition, current issues and challenges are also discussed to identify promising areas for future research.
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| An Introduction to Genetic Algorithms | 1996 | 11,231 |
| Wrappers for feature subset selection | 1997 | 8,991 |
| An introduction to variable and feature selection | 2003 | 7,858 |
| A discrete binary version of the particle swarm algorithm | 2002 | 4,768 |
| Floating search methods in feature selection | 1994 | 3,112 |
| A Practical Approach to Feature Selection | 1992 | 2,996 |
| Introduction to Machine Learning | 2019 | 1,658 |
| Feature subset selection using a genetic algorithm | 1998 | 1,369 |
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Investigating the impact of data normalization on classification performance | 2019 | 1,735 |
Links
Topics
| Evolutionary Algorithms and Applications | Computer Science |
| Metaheuristic Optimization Algorithms Research | Computer Science |
| Neural Networks and Applications | Computer Science |
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