ANALYSIS OF EMAIL INTO SPAM AND HAM USING MULTINOMIAL NAÏVE BAYES
A. N. ARULARASAN
, RAVIRAJAN S R , DHIVAKARAN K , ASHOK KUMAR V
Spam, ham, Spam detection, Multinomial Naïve Bayes , Bayes Theorem ,Phishing
The most difficult problems in social networks is spam identification. (OSNs). In this study, spam on these sites is found using a supervised technique. The choice of the intended features and the application of the right classifier both had an impact on the precision of supervised techniques. The first element is also handled in a novel way. With the intention of selecting the desired characteristic from a range of features, this technique combines association rule mining and genetic algorithms. The second component, on the other hand, makes use of a lot of well-liked predictors. The efficacy of the proposed feature selection method on the classifiers precision is demonstrated by the evaluation of the proposed method on three datasets. The combined sum of both methodologies versus the fundamental techniques are 87.98% and 95.23%, respectively
"ANALYSIS OF EMAIL INTO SPAM AND HAM USING MULTINOMIAL NAÏVE BAYES", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.137-142, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001021.pdf
Volume 11
Issue 2,
February-2024
Pages : 137-142
Paper Reg. ID: TIJER_150955
Published Paper Id: TIJERB001021
Downloads: 000279
Research Area: Science and Technology
Country: Thiruvallur, TamilNadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
