• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Variable Selection of Feature Pattern using SVM-based Criterion with Q-Learning in Reinforcement Learning


Chayoung Kim, Journal of Internet Computing and Services, Vol. 20, No. 4, pp. 21-27, Aug. 2019
10.7472/jksii.2019.20.4.21, Full Text:
Keywords: Support-Vector Machine, RNA sequencing Big-Data, Support Vector Machine-Recursive Feature Elimination, Q-learning, Reinforcement Learning

Abstract

Selection of feature pattern gathered from the observation of the RNA sequencing data (RNA-seq) are not all equally informative for identification of differential expressions: some of them may be noisy, correlated or irrelevant because of redundancy in Big-Data sets. Variable selection of feature pattern aims at differential expressed gene set that is significantly relevant for a special task. This issues are complex and important in many domains, for example. In terms of a computational research field of machine learning, selection of feature pattern has been studied such as Random Forest, K-Nearest and Support Vector Machine (SVM). One of most the well-known machine learning algorithms is SVM, which is classical as well as original. The one of a member of SVM-criterion is Support Vector Machine-Recursive Feature Elimination (SVM-RFE), which have been utilized in our research work. We propose a novel algorithm of the SVM-RFE with Q-learning in reinforcement learning for better variable selection of feature pattern. By comparing our proposed algorithm with the well-known SVM-RFE combining Welch’ T in published data, our result can show that the criterion from weight vector of SVM-RFE enhanced by Q-learning has been improved by an off-policy by a more exploratory scheme of Q-learning.


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Cite this article
[APA Style]
Kim, C. (2019). Variable Selection of Feature Pattern using SVM-based Criterion with Q-Learning in Reinforcement Learning. Journal of Internet Computing and Services, 20(4), 21-27. DOI: 10.7472/jksii.2019.20.4.21.

[IEEE Style]
C. Kim, "Variable Selection of Feature Pattern using SVM-based Criterion with Q-Learning in Reinforcement Learning," Journal of Internet Computing and Services, vol. 20, no. 4, pp. 21-27, 2019. DOI: 10.7472/jksii.2019.20.4.21.

[ACM Style]
Chayoung Kim. 2019. Variable Selection of Feature Pattern using SVM-based Criterion with Q-Learning in Reinforcement Learning. Journal of Internet Computing and Services, 20, 4, (2019), 21-27. DOI: 10.7472/jksii.2019.20.4.21.