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Questions related to the Locally Interpretable Model-Agnostic Explanations (LIME) method of explaining black-box machine learning models.
4
votes
Accepted
Understanding functioning of LIME(Local Interpretable Model-agnostic Explanations)
When using LIME to explain an instance $i$, we create fake data because through them and their subsequent labelling we can infer how our complex learner $L$ would behave in neighbourhood of $i$ through … Do note that LIME is not strongly affect by the number of available "true" training examples as ultimately the explainer is trained on the "fake data". …
2
votes
Accepted
How to interpret probabilities together with output from R lime package?
What LIME does is fitting a "simple and interpretable" model on top of "complex and uninterpretable" model. … LIME is not a good tool for this use case. LIME is a really great tool but it is not a silver bullet when it comes to ML interpretation. …
2
votes
Accepted
LIME Shows Very High Probability Score, But Breakdown Has All Negative Factors
The results from local explainer by LIME can disagree (on occasion substantially) with the results of the global model. … More details: LIME is training a model in the "neighbourhood" of the point we are trying to explain. …
3
votes
Accepted
Why LIME does not show prediction probability for the other class?
The second numbers encapsulate the behaviour of the linear model used by LIME in the neighbourhood of the sample-point we trying to explain. … (Notice that LIME usually does not employ all the available features when making an explanation, we usually set the num_features to be smaller than the total number of available features.) …
2
votes
LIME Analysis Linear Model
Using LIME on-top of a linear model will probably have limited utility. … This again might make the LIME explanation different from the one we would get directly from a linear model.
The LIME perturbations themselves might be somewhat misleading here. …
6
votes
H2o interpretability - LIME
LIME will discretize numerical features internally. … Remember that using LIME we are fitting a "simple" model on top of "complex" model. …