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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;