ARCHIVES
Research Article
Text Classification Using Gaussian, Multinomial naïve Bayes and Logistic Regression
Kaalishwar R1
Dr. Sujithra M2
12Department Of Computing, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, India.
Published Online: November-December 2022
Pages: 112-114
Cite this article
No DOIReferences
[1]. Authors: Johnson Kolluri, Shaik Razia, and Soumya Ranjan Nayak. “Text classification using machine learning and deep learning
model”, in arvix.org, June 2020
[2]. Shervin Minaee, NalKalchbrenner, Erik Cambria, NarjesNikzad, MeysamChenaghlu, and Jianfeng Gao. 7. “Deep learning based text
classification: A comprehensive review”, in arvix.org, January 2022
[3]. Kanish Shah, Henil Patel, Devanshi Sanghvi, and Manan Shah. “A comparative analysis of logistic regression, random forest and KNN
models for the text classification”, March 2020
[4]. Hui Li, Zeming Li. “Text Classification Based on Machine Learning and Natural Language Processing Algorithms”, in hindawi,
Volume 2022
[5]. Johnson Kolluri, Shaik Razia, and Soumya Ranjan Nayak.”Text classification using machine learning and deep learning models”,
International Conference on Artificial Intelligence in Manufacturing and Renewable Energy(ICAMRE)2019
model”, in arvix.org, June 2020
[2]. Shervin Minaee, NalKalchbrenner, Erik Cambria, NarjesNikzad, MeysamChenaghlu, and Jianfeng Gao. 7. “Deep learning based text
classification: A comprehensive review”, in arvix.org, January 2022
[3]. Kanish Shah, Henil Patel, Devanshi Sanghvi, and Manan Shah. “A comparative analysis of logistic regression, random forest and KNN
models for the text classification”, March 2020
[4]. Hui Li, Zeming Li. “Text Classification Based on Machine Learning and Natural Language Processing Algorithms”, in hindawi,
Volume 2022
[5]. Johnson Kolluri, Shaik Razia, and Soumya Ranjan Nayak.”Text classification using machine learning and deep learning models”,
International Conference on Artificial Intelligence in Manufacturing and Renewable Energy(ICAMRE)2019
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