Detecting Email Spam
Modern spam filtering software continuously struggles to categorise the emails correctly. Unwanted spam & promotional communication is the toughest of them all. Spam communication algorithms must be iterated continuously since there is an ongoing battle between spam filtering software and anonymous spam & promotional mail senders. Naive Bayes Algorithm in data analytics forms the base for text filtering in Gmail, Yahoo Mail, Hotmail & all other platforms.
Like Naive Bayes, other classifier algorithms like Support Vector Machine, or Neural Network also get the job done! Before we begin, here is the dataset for you to download:
Email Spam Filtering Using Naive Bayes Algorithm This would be a zipped file, attached in the email. Please allow users to download this data.
Machine Learning Algorithm
The Naive Bayes Classifier Formula
One of the most simple yet powerful classifier algorithms, Naive Bayes is based on Bayes’ Theorem Formula with an assumption of independence among predictors. Given a Hypothesis A and evidence B, Bayes’ Theorem calculator states that the relationship between the probability of Hypothesis before getting the evidence P(A) and the probability of the hypothesis after getting the evidence.