iancovert / shapley-regressionLinks
For calculating Shapley values via linear regression.
☆70Updated 4 years ago
Alternatives and similar repositories for shapley-regression
Users that are interested in shapley-regression are comparing it to the libraries listed below
Sorting:
- An amortized approach for calculating local Shapley value explanations☆98Updated last year
- Neural Additive Models (Google Research)☆71Updated 3 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- A benchmark for distribution shift in tabular data☆55Updated last year
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 6 months ago
- Influence Estimation for Gradient-Boosted Decision Trees☆29Updated last year
- For calculating global feature importance using Shapley values.☆272Updated last week
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆84Updated last year
- Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)☆152Updated 2 years ago
- A repo for transfer learning with deep tabular models☆104Updated 2 years ago
- A collection of algorithms of counterfactual explanations.☆50Updated 4 years ago
- Rule Extraction Methods for Interactive eXplainability☆46Updated 3 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 3 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆83Updated 2 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆67Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆70Updated 2 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation☆133Updated 2 months ago
- Conditional calibration of conformal p-values for outlier detection.☆36Updated 2 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆66Updated 5 months ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆68Updated 8 months ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆247Updated 11 months ago
- A package for conformal prediction with conditional guarantees.☆61Updated 5 months ago
- Multi-Objective Counterfactuals☆42Updated 3 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated last year
- Local explanations with uncertainty 💐!☆40Updated last year
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year