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In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

Home Page: https://doi.org/10.3390/make3030027

License: MIT License

Python 12.55% Jupyter Notebook 87.45%
breast-cancer-dataset python3 random-forest classifiers neural-networks scikit-learn clusters xai explainable-ai explainable-ml

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Hi, thank you very much for sharing the code.
But there is a problem I want to ask, that is, after improvement, the contribution of each feature of the advanced interpretation result is the same. I don’t know whether such a result still has interpretive significance.

error when reproducing the results

Thank you for the great paper.

When I was running the code in experiments_bc_rf.py, I got an error in line 80

This method as_pyplot_to_figure belongs to Explanation object but not to explainer_tabular. LimeTabularExplainer. It seems to me that these two objects are independent from each other. Have I missed anything? Could you please advise how to reproduce the result correctly?

Here is the Colab I used.

Support for python 3.6

Dear Sir,

Currently, there is no support for Python 3.6. So how can I use this code? I am interested in using code for project work. Urgently needed.

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