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Email Spam Classification Using Machine Learning

EasyChair Preprint no. 7908

7 pagesDate: May 5, 2022


Email is a great medium of communication which is very reliable and many people use it to communicate for various purposes. Almost everyone who is part of this technical world must have at least one email account. Sometimes we receive spam mails which are tedious for us. To find these spam or not spam mails, we use Naïve Bayes, Support Vector Machine, Decision tree, and Random Forest algorithms It is done by finding the their precision, accuracy, recall, F-score and AUC values ​​and comparing all the models with these known values ​​which show which model is the best model for classification of e-mail spam.

Keyphrases: Classification, E-mail spam, Machine Learning Algorithms

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Naman Airan and Purushottam Lal Bhari},
  title = {Email Spam Classification Using Machine Learning},
  howpublished = {EasyChair Preprint no. 7908},

  year = {EasyChair, 2022}}
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