Changes in version 1.5.10 (2019-02-28) - Updated CITATION. - Removed unnecessary dependency. Changes in version 1.5.9 (2018-11-12) - Dropped old interface. - Improved distance calculations. - ... argument added to plot. Changes in version 1.5.8 (2018-09-24) - Allow setting seed before sampling in sample_locally2 to make results reproducible. - Add new explainer: local_permutation_importance function. - Fixed problems with mlr dependency. - Add shortcut function for DALEX explainers: local_approximation. Changes in version 1.5.7 (2018-06-03) - New method of sampling ("normal"). Changes in version 1.5.6 - Waterfall plots can be viewed in a Shiny app. Changes in version 1.5.5 - Fixed bug related to standardizing columns in fit_explanation. Changes in version 1.5.4 (2018-05-13) - Old interface dropped. Changes in version 1.5.3 (2018-05-05) - Minor fix to euclidean_kernel function. - Default kernel in fit_explanation is now gaussian_kernel. - Order of arguments changed in add_predictions and data arguments defaults to NULL. - Variables are standardized after predictions are added, before explanation model is fitted in fit_explanation function. Changes in version 1.5.2 - Print functions for results of sample_locally, add_predictions and fit_explanation. Changes in version 1.5.1 - New, LIME-like method of sampling as an option in sample_locally. Changes in version 1.5.0 - Observations in simulated dataset can now be weighted according to their distance from the explained instance. The distance is defined by kernel argument to fit_explanation function. - Some variables can be excluded from sampling. This is controled via fixed_variables argument to sample_locally function. - Documentation was improved. - Object returned by sample_locally, add_predictions and fit_explanation functions now carry more information (mainly explained instance) so some function calls were simplified (plot_explanation). Changes in version 1.4.2 (2018-04-03) - Fixed bug in variable selection. Changes in version 1.4.1 - Variable selection is now better suited to work with factor/character variables. Changes in version 1.4.0 - Variable selection is now based on LASSO as implemented in glmnet package. - Updated documentation and vignette. Changes in version 1.3.3 - add_predictions also returns black box model object (model element). Changes in version 1.3.2 - Hyperparameters can be also passed to add_predictions function. Changes in version 1.3.1 - fit_explanation is now more flexible, can take a list of hyperparameters for a chosen model. Changes in version 1.3.0 - For classification problems waterfall plots can be drawn on probability or logit scale. Changes in version 1.2.0 - Now using forestmodel package for better factor handling. Changes in version 1.1.2 - Date variables will now be hold constant while performing local exploration. - Improved performance. Changes in version 1.1.1 - add_predictions improved to handle more learners (for example ranger). Changes in version 1.1.0 - Added a NEWS.md file to track changes to the package. - sample\_locally uses data.table for faster local exploration. Changes in version 1.0.0 - Cheatsheet added. - First package release.