gtraskas / spamIt

A spam filter in Python using Naive Bayes algorithm

spamIt

spamIt is a spam filter in Python using the Naive Bayes algorithm.

Check Modules

Use the check_modules.py to check your system for the required dependencies.

Download Dataset

Run get_data.py to download a set of spam and ham actual emails in your machine, unzip the compressed files, read the text and load it into a Pandas dataframe. Convert the dataframe to a Pickle object.

Clean the Data

Remove the punctuation, urls and numbers, and convert the words to lower case.

Prepare the Data

Split the text into individual words, stem each word and remove english stop words.

Machine Learning

Vectorize Words and Split Data to Train/Test Sets

Transform the words into a tf-idf matrix with the sklearn TfIdf transformation and create train/test sets.

Train a Classifier

Train a Naive Bayes classifier and evaluate the performance with the accuracy score.

Identify the Most Powerful Features

Print the most important features.

Play

Try out the classifier feeding it with some examples.