Measuring data importance over ML pipelines using the Shapley value.
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Updated
May 25, 2024 - Python
Measuring data importance over ML pipelines using the Shapley value.
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
將預訓練模型作為待售商品,以模型準確度與訓練集為依據的兩階段預測模型定價框架。
Deep Learning Based Models for Preimplantation Mouse and Human Development
Rank nodes in an FBAS like Stellar using the Shapley value and other node centrality measures.
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Tools to Support Relative Importance Analysis
ML modeling and feature importance analysis conducted to identify/inform company practices related work interference due to mental health.
Explain model and feature dependencies by decomposition of SHAP values
This is the official source code for CVPR 2024 paper [WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concepts]
Hopefully, a compact and general-purpose Python package for Multiperturbation Shapley value Analysis (MSA).
Set of Jupyter notebooks and geospatial data developed by the MAPSPADES project to study desertification in the Algerian steppe using EO data.
Multi-Class Prediction of Obesity Risk ML App
This is a course project predicting the price of Bitcoin and some analysis of its variation.
R package for SHAP plots
Dominance Analysis: Stata Implementation
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Tool for estimating the difficulty of phylogenetic placements
Code to solve the activities on our XAI lectures.
A pip library for calculating the Shapley Value for computing the marginal contribution of each client in a Federated Learning environment.
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