Email Spam Filtering using Text Classification

Email Spam Filtering using Text Classification

Email becomes a powerful tool for communication as it saves a lot of time and cost. It is one of the most popular and secure medium for online transferring and communication messages or data through the web. But, due to the social networks, most of the emails contain unwanted information which is called spam. To identify such spam email is one of the important challenges. In this project we will use PYTHON text classification technique to identify or classify email spam message. We will find accuracy, time and error rate by applying suitable algorithms (such as NaiveBayes, NaiveBayesMultinomial and J48 etc.) on Email Dataset and we will also compare which algorithm is best for text classification. Project URL: https://github.com/Ibrahim278/Email-Spam-Filtering-using-Text-Classification

Guassian NB Results

Random Forest Classification Results

Logistic Regression Results

SVM Results

ROC Curve

Precision Recall Curve

Learning Curve