Alternatives and similar repositories for lime-experiments

Users that are interested in lime-experiments are comparing it to the libraries listed below

• BeenKim / MMD-critic
  ☆135Updated 6 years ago
• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆813Updated 3 years ago
• Jianbo-Lab / L2X
  ☆125Updated 4 years ago
• mbilalzafar / fair-classification
  Python code for training fair logistic regression classifiers.
  ☆191Updated 4 years ago
• ArrasL / LRP_for_LSTM
  Layer-wise Relevance Propagation (LRP) for LSTMs.
  ☆226Updated 5 years ago
• ankurtaly / Integrated-Gradients
  Attributing predictions made by the Inception network using the Integrated Gradients method
  ☆645Updated 3 years ago
• equialgo / fairness-in-ml
  This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
  ☆119Updated 4 years ago
• VigneshSrinivasan10 / interprettensor
  ☆100Updated 7 years ago
• algofairness / fairness-comparison
  Comparing fairness-aware machine learning techniques.
  ☆161Updated 3 years ago
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆51Updated 3 years ago
• ustunb / actionable-recourse
  python tools to check recourse in linear classification
  ☆77Updated 5 years ago
• lopusz / awesome-interpretable-machine-learning
  ☆916Updated 2 years ago
• marcoancona / DeepExplain
  A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…
  ☆760Updated 5 years ago
• albahnsen / CostSensitiveClassification
  CostSensitiveClassification Library in Python
  ☆205Updated 5 years ago
• marcotcr / anchor-experiments
  Experiments for AAAI anchor paper
  ☆66Updated 7 years ago
• fair-preprocessing / nips2017
  ☆26Updated 8 years ago
• dtak / tree-regularization-public
  Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"
  ☆80Updated 8 years ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆85Updated 3 years ago
• kohpangwei / influence-release
  ☆805Updated 5 years ago
• suinleelab / treeexplainer-study
  Code and documentation for experiments in the TreeExplainer paper
  ☆190Updated 6 years ago
• GDPlumb / MAPLE
  Supervised Local Modeling for Interpretability
  ☆29Updated 7 years ago
• blei-lab / deconfounder_tutorial
  ☆87Updated 5 years ago
• ksenia-konyushkova / LAL
  This project contains code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017
  ☆88Updated 3 years ago
• tmadl / semisup-learn
  Semi-supervised learning frameworks for python, which allow fitting scikit-learn classifiers to partially labeled data
  ☆505Updated 4 years ago
• tmadl / highdimensional-decision-boundary-plot
  Estimating and plotting the decision boundary (decision surface) of machine learning classifiers in higher dimensions (scikit-learn compa…
  ☆235Updated 2 years ago
• google / TrustScore
  To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…
  ☆177Updated 2 years ago
• marcoancona / DASP
  Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)
  ☆62Updated 6 years ago
• kimhc6028 / soft-decision-tree
  pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
  ☆302Updated 7 years ago
• ipeirotis / Get-Another-Label
  Quality control code for estimating the quality of the workers in crowdsourcing environments
  ☆71Updated 6 months ago
• amarasovic / interpretability-literature
  ☆263Updated 6 years ago