This project was developed as part of a machine learning course to demonstrate the application of Support Vector Machines (SVMs) for classification tasks and the process of selecting the best kernel for the given data.
- Supports multiple kernels: linear, polynomial, and radial basis function (RBF).
- Easy to use with a straightforward interface for data input and model training.
- Generates performance metrics and visualizations to aid in model evaluation.
