shapley VS DALEX

Compare shapley vs DALEX and see what are their differences.

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shapley DALEX
7 2
210 1,323
- 0.6%
2.7 5.5
10 months ago 2 months ago
Python Python
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

shapley

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

DALEX

Posts with mentions or reviews of DALEX. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-25.
  • Twitter set to accept ‘best and final offer’ of Elon Musk
    3 projects | /r/news | 25 Apr 2022
    Which he will not do, because: a) He can't, it's a black box algorithm. It actually is open source already, but that doesn't mean much as it's useless without Twitter's data https://github.com/ModelOriented/DALEX b) He won't release data that shows the algorithm is racist and amplifies conservative and extremist content. He won't remove such functions because it will cost him billions.
  • [D] What are your favorite Random Forest implementations that support categoricals
    2 projects | /r/MachineLearning | 20 Feb 2021
    There are a couple of ways to use Shapley values for explanations in R. One way is to use DALEX, which also contains a lot of other methods besides SHAP. Another one is iml. I am sure there are several other implementations of SHAP as well.

What are some alternatives?

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

autogluon - Fast and Accurate ML in 3 Lines of Code

captum - Model interpretability and understanding for PyTorch