This project is a machine learning model that is developed in Python for classifying spam SMS messages. This model is trained on a dataset of SMS messages labeled as spam or not spam using the scikit-learn library.
The dataset used for training and testing the model is the SMS Spam Collection dataset from the UCI Machine Learning Repository. It contains more than 5,500 SMS messages, some of which are spam and others are not.
The model is a Naive Bayes classifier which is a simple and effective probabilistic algorithm for classification. The scikit-learn implementation of Naive Bayes is used in this project, specifically the MultinomialNB class.
- Python 3.6 or higher
- scikit-learn
- pandas
- numpy