Evaluation of Text Classification Using Support Vector Machine Compare with Naive Bayes, Random Forest Decision Tree and K-NN-Reference-Cited by-同舟云学术

Evaluation of Text Classification Using Support Vector Machine Compare with Naive Bayes, Random Forest Decision Tree and K-NN

Published:2023 Issue: Volume: Page:321-331
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
Short-container-title:

Author:

Hai Tao^ORCID,Zhou Jincheng^ORCID,Zadeh Shirin Abolfath^ORCID,Adetiloye Oluwabukola A.^ORCID,Li Mingjiang,Uhumuavbi Ikpenmosa^ORCID,Iwendi Celestine^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-37164-6_23

Reference18 articles.

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2. Gao, Y., Sun, S.: An empirical evaluation of linear and nonlinear kernels for text classification using Support Vector Machines. In: 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, Yantai, China, pp. 1502–1505 (2010). https://doi.org/10.1109/FSKD.2010.5569327

3. Lin, X.-d., Peng, H., Liu, B.: Support vector machines for text categorization in chinese question classification. In: 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06), Hong Kong, China, pp. 334–337 (2006). https://doi.org/10.1109/WI.2006.163

4. Hao, P., Ying, D., Longyuan, T.: Application for web text categorization based on support vector machine. In: 2009 International Forum on Computer Science-Technology and Applications, Chongqing, China, pp. 42–45 (2009).https://doi.org/10.1109/IFCSTA.2009.132

5. Wang, Q., Liu, Z., Zhang, T., Li, Y.: Short text classification based on cross-connected GRU kernel mapping support vector machine. In: 2021 2nd Asia Symposium on Signal Processing (ASSP), Beijing, China, pp. 201–207 (2021).https://doi.org/10.1109/ASSP54407.2021.00038