- Add support for image explanation. The dispatch will be on paths pointing to valid image files. Image explanations can be visualised using
- Add support for neural networks from the
as_regressor() for ad-hoc specification of the model type in case the heuristic implemented in
lime doesn’t hold.
as_classifier() also lets you add/overwrite the class labels.
gower as the new default similarity measure for tabular data
bin_continuous = FALSE the default behavior is now to sample from a kernel density estimation rather than assume a normal distribution.
- Fix bug when numeric features in the training data were constant (#56)
- Fix bug when plotting regression explanations with
- Logical columns in tabular data is now supported (#75)
- Overhaul of
plot_text_explanation() with better formatting and scrolling support for many explanations
- All plots now show the fit of the explainer so the user can assess the quality of the explanation
- Added a
NEWS.md file to track changes to the package.
- Fixed bug when explaining regression models, due to drop=TRUE defaults (#33)
- Integer features are no longer converted to numeric during permutations (#32)
- Fix bug when working with xgboost and tabular predictions (@martinju #1)
- Training data can now contain
NA values (#8)
- Keep ordering when plotting with
- Fix support for mlr by extracting predictions correctly
- Added support for
h2o (@mdancho84) (#40)
- Throws meaningful error when all permutations have 0 similarity to original observation (#47)
- Explaining data can now contain
NA values (#45)
- Support for
POSIXt columns. They will be kept constant during permutations so that
lime will explain the model behaviour at the given timepoint based on the remaining features (#39).
plot_explanations() for an overview plot of a large explanation set