DiCE VS shapley

Compare DiCE vs shapley and see what are their differences.

DiCE

Generate Diverse Counterfactual Explanations for any machine learning model. (by interpretml)
counterfactual-explanations explainable-ml xai interpretable-machine-learning Deep Learning Machine Learning explainable-ai
Source Code
interpretml.github.io
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shapley

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021). (by benedekrozemberczki)
Shapley shapley-value Owen voting-classifier Machine Learning Classifier random-forest random-forest-classifier explainable-ml explainable-ai Ensemble ensemble-learning Deep Learning voting-game game-theory game-theory-toolbox weighted-voting-games
Source Code
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DiCE shapley
2 7
1,270 210
2.1% -
8.2 2.7
10 days ago 10 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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DiCE

Posts with mentions or reviews of DiCE. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-31.
  • [D] Have researchers given up on traditional machine learning methods?
    2 projects | /r/MachineLearning | 31 Jan 2023
    - all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
  • [R] The Shapley Value in Machine Learning
    1 project | /r/MachineLearning | 25 Feb 2022
    Counter-factual and recourse-based explanations are alternative approach to model explanations. I used to work in a large financial institution, and we were researching whether counter-factual explanation methods would lead to better reason codes for adverse action notices.

shapley

Posts with mentions or reviews of shapley. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DiCE and shapley you can also consider the following projects:

OmniXAI - OmniXAI: A Library for eXplainable AI

DALEX - moDel Agnostic Language for Exploration and eXplanation

CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code

AIX360 - Interpretability and explainability of data and machine learning models

sagemaker-explaining-credit-decisions - Amazon SageMaker Solution for explaining credit decisions.

interpret - Fit interpretable models. Explain blackbox machine learning.

awesome-shapley-value - Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

harakiri - Help applications kill themselves

stranger - Chat anonymously with a randomly chosen stranger

csle - A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

DiCE vs OmniXAI shapley vs DALEX DiCE vs CARLA shapley vs autogluon DiCE vs AIX360 shapley vs sagemaker-explaining-credit-decisions DiCE vs interpret shapley vs awesome-shapley-value DiCE vs harakiri shapley vs AIX360 DiCE vs stranger shapley vs csle