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I recently become familiar with Interpretable ML and I found some libraries like LIME. I would be thankful if you can suggest to me some libraries and what are the advantages of each library.

Amin
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    I have been maintaining a relevant answer in Artificial Intelligence SE, [Which explainable artificial intelligence techniques are there?](https://ai.stackexchange.com/questions/12870/which-explainable-artificial-intelligence-techniques-are-there/24138#24138) – desertnaut Mar 22 '21 at 22:06

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A couple of the most common Python packages for interpretable machine learning:

  • Lime - Can explain the prediction of any machine learning classifier.

  • SHAP - A game-theoretic approach to explain the output of any machine learning model.

  • ELI5 - Explain the weights and predictions of a variety of machine learning models.

Brian Spiering
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I will suggest Dalex as it has a very easy workflow and has both Python and R APIs.

Also Interpret-ML from Microsoft has very good features.

tfkLSTM
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