1. An ensemble of intelligent water drop algorithm for feature selection optimization problem.
- Author
-
Alijla, Basem O., Lim, Chee Peng, Wong, Li-Pei, Khader, Ahamad Tajudin, and Al-Betar, Mohammed Azmi
- Subjects
FEATURE selection ,MOTION detectors ,SWARM intelligence ,TEXT mining ,GENE expression - Abstract
Master River Multiple Creeks Intelligent Water Drops (MRMC-IWD) is an ensemble model of the intelligent water drop, whereby a divide-and-conquer strategy is utilized to improve the search process. In this paper, the potential of the MRMC-IWD using real-world optimization problems related to feature selection and classification tasks is assessed. An experimental study on a number of publicly available benchmark data sets and two real-world problems, namely human motion detection and motor fault detection, are conducted. Comparative studies pertaining to the features reduction and classification accuracies using different evaluation techniques (consistency-based, CFS, and FRFS) and classifiers (i.e., C4.5, VQNN, and SVM) are conducted. The results ascertain the effectiveness of the MRMC-IWD in improving the performance of the original IWD algorithm as well as undertaking real-world optimization problems. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF