Soft voting technique to improve the performance of global filter based feature selection in text corpus-Reference-Cited by-同舟云学术

Soft voting technique to improve the performance of global filter based feature selection in text corpus

Published:2018-11-21 Issue:4 Volume:49 Page:1597-1619
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Agnihotri Deepak^ORCID,Verma Kesari,Tripathi Priyanka,Singh Bikesh Kumar

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s10489-018-1349-1.pdf

Reference50 articles.

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2. Agnihotri D, Verma K, Tripathi P (2016) Computing correlative association of terms for automatic classification of text documents. In: Proceedings of the third international symposium on computer vision and the internet, ACM, pp 71–80

3. Agnihotri D, Verma K, Tripathi P (2016b) Computing symmetrical strength of n-grams: a two pass filtering approach in automatic classification of text documents. SPRINGERPLUS 5(942):1–29

4. Agnihotri D, Verma K, Tripathi P (2017) An automatic classification of text documents based on correlative association of words. J Intell Inform Syst. https://doi.org/10.1007/s10844-017-0482-3

5. Agnihotri D, Verma K, Tripathi P (2017) Mutual information using sample variance for text feature selection. In: Proceedings of the 3rd international conference on communication and information processing, ACM, New York, NY, USA, ICCIP ’17, pp 39–44. https://doi.org/10.1145/3162957.3163054

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