Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME

doi:doi:10.57702/scu8r8vk

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Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME

The paper introduces a new version of ALIME, which uses a decision tree instead of a linear model as the locally interpretable model.

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Cite this as

Niloofar Ranjbar, Reza Safabakhsh (2024). Dataset: Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME. https://doi.org/10.57702/scu8r8vk

DOI retrieved: December 3, 2024

Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Author	Niloofar Ranjbar
More Authors	Reza Safabakhsh
Homepage	https://github.com/nranjbar/interpretable_machine_learning