Overview

This repository contains a python implementation of the Least Squares Support Vector Machine (LSSVM) model on CPU and GPU, you can find a bit of theory and usage of the code on the LSSVC.ipynb jupyter notebook. For a more enjoyable view of the notebook: https://nbviewer.jupyter.org/github/RomuloDrumond/LSSVM/blob/master/LSSVC.ipynb

To install dependencies run pip install -r requirements.txt on the main directory.

Important libraries used:

• Pandas, for loading and preprocessing of the data;
• Sklearn, for scaling features;
• Numpy, for matrices computation on CPU version;
• PyTorch, for matrices computations on GPU version;
• Scipy, for the fast cdist function;