pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
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Updated
Jun 7, 2024 - Python
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
A Mathematica Package for Cooperative Game Theory
A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Explain model and feature dependencies by decomposition of SHAP values
Measuring data importance over ML pipelines using the Shapley value.
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。
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
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.
A Julia package for interpretable machine learning with stochastic Shapley values
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.
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
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