Why do employees leave? This project first compares the predictive performance of three different models, then uses the best model to help reveal the top contributing factors.
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Updated
May 24, 2022 - Jupyter Notebook
Why do employees leave? This project first compares the predictive performance of three different models, then uses the best model to help reveal the top contributing factors.
Python/Jupyter Notebook to my Bachelor-Thesis in Computer Science. Explains contributions of features that are not part of a Machine Learning model by using Transfer Learning and Shapley Values/SHAP.
API backend to deploy a machine learning model to the web
A radiomic interpretation tool based on Shapley values
API for ShapEmotionsCorrection project
A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
Analysis of baseball stats using ML w/ feature explainability
This is a visual and interactive part of a bigger Adults project. Income prediction is based on Random Forest model. Front part is created with dash framework
Final Year Project KCL
[IJCAI 2024] Redefining Contributions: Shapley-Driven Federated Learning
Graph neural network library
Msc. Thesis: Revising the clinical criteria for Dementia using explainable machine learning.
Final Project for CS231C (Computer Vision and Image Analysis of Art)
Heart disease prediction by exploring different models, and feature importance visualization
ML implementations in Multi-scale model for lignin biosynthesis in Populus Trichocarpa
A Julia port of the fastshap package in R
Using SHAP values to explain model features
An investigation on the use of shapley explanations for unsupervised anomaly-detection models
Reference implementation of the paper Redundancy-aware unsupervised ranking based on game theory - application to gene enrichment analysis
Migration networks and housing prices analysis and ML tools
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