An empirical study to estimate the stability of random forest classifier on the hybrid features recommended by filter based feature selection technique-Reference-Cited by-同舟云学术

An empirical study to estimate the stability of random forest classifier on the hybrid features recommended by filter based feature selection technique

Published:2019-07-02 Issue:2 Volume:11 Page:339-358
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Darshan S. L. Shiva^ORCID,Jaidhar C. D.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s13042-019-00978-7.pdf

Reference62 articles.

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4. Aman N, Saleem Y, Abbasi FH, Shahzad F (2017) A hybrid approach for malware family classification. In: Applications and techniques in information security, vol 719. Springer, Singapore, pp 169–180. https://doi.org/10.1007/978-981-10-5421-1_14

5. Amin M (2016) A survey of financial losses due to malware. In: Proceedings of the second international conference on information and communication technology for competitive Strategies. ACM, pp 145:1–145:4. https://doi.org/10.1145/2905055.2905362

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