This project implements a machine learning model to classify messages as spam or not. It utilizes multiple machine learning classifiers, and the Multinomial Naive Bayes classifier has shown to provide the best results for this task.
- Utilizes various machine learning classifiers for spam detection.
- Multinomial Naive Bayes classifier achieves the best performance in identifying spam messages.
- Implements model persistence using the pickle module.
- Provides a simple and efficient way to classify messages as spam or not.
To run the spam classifier:
- Clone this repository:
git clone https://github.com/Astik-Gorai/spamSMS_Predictor.git
- Install the required dependencies:
pip install -r requirements.txt
- Run the main script:
streamlit run app.py