doi: 10.4304/jsw.9.2.515-522
Research and Application of Data Mining Feature Selection Based on Relief Algorithm
- 1 Scientific Research Office, Chongqing University of Science and Technology, Chongqing, 40133,China
- 2 School of Electric and Information Engineering, Chongqing University of Science and Technology, Chongqing, 40133,China
Abstract
To choose the best features in data mining issues,the Relief Feature Selection Algorithm is proposed toimplement the feature selection in this paper. Firstly, thedata of Ionosphere from the UCI (University of California -Irvine) database is used to do a simulation experiment;secondly, the proposed method is employed to do featureselection for voice signal. In this case study, the study startsfrom the 24-dimensional parameters of MFCC (MelFrequency Cepstrum Coefficient), the most importantparameters of MFCC can be found in the voice signal; then,the 24-dimensional parameters of MFCC can be combinedand optimized in the case of recognition rate not muchchanged. The experimental results show that the methodextracts out the best features. Therefore, the researchprovides a new direction to feature extraction for speechrecognition process.
Keywords
- relief algorithm
- feature selection
- dat
How to Cite
Lun Gao, Taifu Li, Lizhong Yao, and Feng Wen, "Research and Application of Data Mining Feature Selection Based on Relief Algorithm," Journal of Software, vol. 9, no. 2, pp. 515-522, 2014. https://doi.org/ 10.4304/jsw.9.2.515-522
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).