Function reference • lime

Creating explanations These functions are the bread and butter of lime and is used to create an explainer from a model and apply it to an observation.
`lime()`	Create a model explanation function based on training data
`explain()`	Explain model predictions
`predict_model()` `model_type()`	Methods for extending limes model support
`as_classifier()` `as_regressor()`	Indicate model type to lime
Investigating explanations While an explanation can be inspected through its tabular output format it is often much more powerful through different visualisations.
`plot_features()`	Plot the features in an explanation
`plot_explanations()`	Plot a condensed overview of all explanations
`plot_image_explanation()`	Display image explanations as superpixel areas
`plot_text_explanations()`	Plot text explanations
`interactive_text_explanations()` `text_explanations_output()` `render_text_explanations()`	Interactive explanations
Miscellaneous This set of functions are sometimes needed in more specialised tasks
`default_tokenize()`	Default function to tokenize
`plot_superpixels()`	Test super pixel segmentation
`stop_words_sentences`	Stop words list
`test_sentences`	Sentence corpus - test part
`train_sentences`	Sentence corpus - train part
`lime-package` `_PACKAGE`	lime: Local Interpretable Model-Agnostic Explanations

Reference