ml-svm-spamassassin-spam-classifier

This jupyter notebook application fits a Support Vector Machine model to classify emails as spam or not using the SpamAssassin Public Corpus data, and also provides the ability to predict new emails.

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Setup

• Clone this repo to your desktop.

• Extract the data.rar file to the root directory of this project.

• Create a new anaconda environment with all the requirements using the following command:

  conda env create -f environment.yml
  

• Activate the environment using (windows)

  activate spam-classifier-env
  

  or if you are on a linux machine

  source activate spam-classifier-env
  

• Run jupyter notebook from the root directory to open up the notebook in your browser.

Usage

To predict new emails:

• Run all cells in the jupyter notebook to train the model.

• Add the txt file(s) of the new raw sample(s) you want to predict to the "data\samples" directory. (Note: Make sure the data.rar file has already been extracted.)

• Run predictSamples(filenames) where "filenames" is a python list of the names of all the samples you want to predict, such as:

  filenames = ['emailSample1.txt', 'emailSample2.txt']