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Demonstrating the use of explainable methods by interpreting the decisions of several neural network models.

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bostickt201/-Interpreting-Breast-Cancer-Detection-Models-w-XAI

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-Interpreting-Breast-Cancer-Detection-Models-w-XAI

This repo was originally created as a final project for DS340W (Applied Data Sciences).

The purpose of this project is to demonstrate the use of several local and global explainable methods by interpreting the decisions of a number of neural network models, each varying in complexity. Each model is trained using data from the Wisconsin Breast Cancer (Diagnostic) Dataset that can be found here on Kaggle:

https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data

All relevent files are located either within a folder labeled 'dropout' or with 'dropout' specified in the file's name.

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Demonstrating the use of explainable methods by interpreting the decisions of several neural network models.

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