A survey of comparative study of detection of spam in machine learning

A spam detection is a method which is used for finding scrap, possible virus infected and undesirable and to avert mails before reaching the applicant's mailbox. Similar to former cases of sifting projects, a spam sifter is on the look out for distinct norms to make a decision. Already some of the ML algorithms have been used for spam detection. Stemmer with count_vectorizer, Lemmatizer with count_vectorizer, poterstremmer with TFldf_vectorizer etc. They all have succeeded in spam detection but it can improve the time taken for the process. So we are going to tri-spam classifying using naive bayes classifier which will bring as accuracy of 94%.