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Pytorch implementation of "DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data".

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DeepSMOTE

DeepSMOTE paper: https://arxiv.org/pdf/2105.02340.pdf

Code

This repository contains sample code to implement DeepSMOTE. The first file, DeepSMOTE_MNIST.py, contains code to train a model on the MNIST dataset. The second file, GenerateSamples, provides code to generate samples on a trained model.

Data and Pre-Trained Models

Sample training images and labels, as well as saved models are available for download at: https://drive.google.com/drive/folders/1GRrpiR0CJpcfpjBKO18FLjombxgqH9cK?usp=sharing

Dependencies

The code was written with: Numpy 1.17; Python 3.6; Pytorch 1.3; and Scikit learn 0.24.1.

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Pytorch implementation of "DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data".

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