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LIMElime.data-imaginist.comLIME is an R package that explains the predictions of black-box classifiers using the Local Interpretable Model-agnostic Explanations (LIME) approach, identifying the features that drove each prediction. It works with many models through idiomatic R interfaces (caret, parsnip, mlr) and can be extended to any model by supplying a predict_model and model_type method. The package also provides capabilities for explaining image and text models with visualizations and interactive tools, and is available on CRAN and GitHub as an R port of the original Python LIME project.
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Excerpts where LIME appeared in the AI's answer
LIME (Local Interpretable Model-agnostic Explanations): LIME tests what happens to a model's predictions when you playfully perturb the inputs of a single prediction.
LIME (Local Interpretable Model-agnostic Explanations): LIME tests what happens to a model's predictions when you playfully perturb the input data around a single prediction.
Excerpts where LIME appeared in the AI's answer
LIME (Local Interpretable Model-agnostic Explanations): Best for fast, intuitive local explanations by approximating the black-box model with a simple linear model right around a single data point.
LIME is another popular option. It explains a single prediction by approximating the model locally with a simpler model.
Excerpts where LIME appeared in the AI's answer
LIME hones in on a single prediction by approximating the complex black-box model locally with a simpler, interpretable linear model.
LIME - Explains individual predictions by approximating the model locally with an interpretable surrogate.
