Universiti Teknologi Malaysia Institutional Repository

A review of harmony search algorithm-based feature selection method for classification

Yusup, N. and Zain, A. N. and Latip, A. A. (2019) A review of harmony search algorithm-based feature selection method for classification. In: 2nd International Conference on Data and Information Science, ICoDIS 2018, 15-16 Nov 2018, Bandung, Indonesia.


Official URL: https://dx.doi.org/10.1088/1742-6596/1192/1/012038


In high dimensional datasets, feature selection plays a significant task for dimensionality reduction and classification. During feature selection process, only the most relevant features in the datasets will be selected. A good feature selection technique can reduce computation cost and increased classification performance. In this paper, we discuss the performance of feature selection with Harmony Search (HS) algorithm for classification in various applications. From the review, it can be concluded that feature selection with HS gives a good performance in many research areas as compared to other nature inspired metaheuristics algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:data mining, feature extraction, genetic algorithms
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:88533
Deposited By: Narimah Nawil
Deposited On:15 Dec 2020 08:19
Last Modified:15 Dec 2020 08:19

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