A Combine Model for Email Classification in Hindi Language using Supervised Learning (NB, K-NN, DT, SVM)

https://doi.org/10.55529/jaimlnn.23.17.23

Authors

  • Dr. Ishaan Tamhankar Assistant Professor, Vimal Tormal Poddar BCA College

Keywords:

Naïve Bayes (NB), K-Nearest Neighbor (K-NN), Decision Tree (DT), Support Vector Machine (SVM).

Abstract

Email communication is necessary in today's environment, yet unwanted emails create issue in such communication. The current study focuses on developing an Email classification model for the use of classifiers approaches. The goal of this research is to classification of emails based on features. For classification especially in Hindi language of the email dataset Different machine learning classifiers such as Naïve Bayes, Decision Tree, K-Nearest Neighbor and Support Vector Machine used in research work as well as we used combined model also for optimum accuracy.

Published

2022-05-02

How to Cite

Dr. Ishaan Tamhankar. (2022). A Combine Model for Email Classification in Hindi Language using Supervised Learning (NB, K-NN, DT, SVM). Journal of Artificial Intelligence,Machine Learning and Neural Network , 2(03), 17–23. https://doi.org/10.55529/jaimlnn.23.17.23

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