Requirements
Python 3.x Pandas
Usage
Clone this repository using git clone https://github.com/aan2907/Spam-Mail-Classifier-NB.git Navigate to the directory using cd Spam-Mail-Classifier-NB Run the program using python NB.py
In our project, we train Naive Bayes algorithm for e-mail spam filtering on the training datasets and test its performance. The training dataset is a set of emails classified as spam or ham, ham being the emails not detected as spam. On sending a new email, the model predicts whether the email in question is spam or not. Several machine learning algorithms have been used in spam email filtering, but Naive Bayes algorithm is particularly popular in commercial and open-source spam filters. This is because of its simplicity, which makes them easy to implement and just need short training time or fast evaluation to filter email spam. The performance of the datasets is evaluated based on their accuracy. Finally, the program displays the predicted label (spam or non-spam) in the GUI along with a confidence score. This enables the user to make an informed decision about whether to take action on the message.
Credits: Govind