Project information
- Category: Classification
- Project date: March, 2021
- Project URL: SMS Spam Classification Repository
Project Description
The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research. The goal of this project is to develop a machine learning model that can accurately classify SMS messages as either "spam" or "ham". This is important because spam messages can be a nuisance and even pose a security risk if they contain phishing scams or malicious links. By accurately identifying spam messages, users can avoid them and better protect their personal information. I achieved an accuracy of 0.97 by using the Multilayer Perceptron.
Methods Used
- Data Processing / Data Cleaning
- Data Analysis
- Data Visualization
- Text Preprocessing
- Predictive Modeling and Hyperparameter Tuning
- Evaluating Model Results