Spam Classifier

  • Unique Paper ID: 149967
  • Volume: 7
  • Issue: 2
  • PageNo: 106-109
  • Abstract:
  • 1.SMS classification is detecting spam and ham using Naïve Bayes classifier. 2.Naive Bayes classifier is a machine learning algorithm which uses the Bayes theorem in solving a classification problem. 3.It’s one of the simplest probabilistic models and it is used as a benchmark for comparing the performance of other classification algorithms. 4.This algorithm is prefixed with the word ‘Naive’ since this algorithm strongly assume the conditional independence between the features. 5. This project incorporates the techniques of Naive Bayes classification to classify spam and ham messages.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{149967,
        author = {Rishabh Chaturvedi and Harsh Raj},
        title = {Spam Classifier},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {2},
        pages = {106-109},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=149967},
        abstract = {1.SMS classification is detecting spam and ham using Naïve Bayes classifier.
2.Naive Bayes classifier is a machine learning algorithm which uses the Bayes theorem in solving a classification problem. 
3.It’s one of the simplest probabilistic models and it is used as a benchmark for comparing the performance of other classification algorithms.
4.This algorithm is prefixed with the word ‘Naive’ since this algorithm strongly assume the conditional independence between the features.
5. This project incorporates the techniques of Naive Bayes classification to classify spam and ham messages.
},
        keywords = {SPAM CLASSIFIER},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 7
  • Issue: 2
  • PageNo: 106-109

Spam Classifier

Related Articles