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A Method to Clustering the Feature Ranking on Data Classification Using an Ensemble Feature Selection

Nuntawut Kaoungku, the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand, Kittisak Kerdprasop, Nittaya Kerdprasop, the School of Computer Engineering; Knowledge Engineering Research Unit, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand, the School of Computer Engineering; Data Engineering Research Unit, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
2017 International Journal of Future Computer and Communication  

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The aim of this paper is to improve the predictive performance of the classification process by means of building multiple data classification models based on the output from feature selection methods that use ensemble strategy to find the optimal set of features. Currently, the data volume has grown at an extreme rate causing a variety of problems. The big data situation has made automatic analysis tasks such as data classification facing low performance and high computational time problems
more » ... n dealing with big data that are huge in both volume and dimensions. In this research work, we tackle the big data problem in the high dimensionality aspect. We propose an ensemble method to reduce data dimension by means of feature clustering to rank the potential features and also return suitable subset of features for further classifying the training data. The two paradigms of feature selection based on ensemble strategy are proposed and evaluated. Experimental results confirm the efficacy of our proposed feature ensemble method.
doi:10.18178/ijfcc.2017.6.3.494 fatcat:pi6wt5otczalfkhpohshcvqzvu
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Nuntawut Kaoungku, the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand, Kittisak Kerdprasop, Nittaya Kerdprasop, the School of Computer Engineering; Knowledge Engineering Research Unit, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand, the School of Computer Engineering; Data Engineering Research Unit, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand. "A Method to Clustering the Feature Ranking on Data Classification Using an Ensemble Feature Selection." International Journal of Future Computer and Communication 6.3 (2017) 81-85