https://github.com/cran/live
Tip revision: 8aed1f23c19d367e5b7d23427a5b7a167af51d2e authored by Mateusz Staniak on 15 January 2020, 05:30:17 UTC
version 1.5.13
version 1.5.13
Tip revision: 8aed1f2
NEWS.md
# live 1.5.13
* Attempted fix for Solaris issues.
# live 1.5.12
* Fixes issues on Windows.
# live 1.5.11
* Update after changes in glmnet.
# live 1.5.10
* Updated CITATION.
* Removed unnecessary dependency.
# live 1.5.9
* Dropped old interface.
* Improved distance calculations.
* ... argument added to `plot`.
# live 1.5.8
* 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`.
# live 1.5.7
* New method of sampling ("normal").
# 1ive 1.5.6
* Waterfall plots can be viewed in a Shiny app.
# live 1.5.5
* Fixed bug related to standardizing columns in `fit_explanation`.
# live 1.5.4
* Old interface dropped.
# live 1.5.3
* 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.
# live 1.5.2
* Print functions for results of sample_locally, add_predictions and fit_explanation.
# live 1.5.1
* New, LIME-like method of sampling as an option in `sample_locally`.
# live 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`).
# live 1.4.2
* Fixed bug in variable selection.
# live 1.4.1
* Variable selection is now better suited to work with factor/character variables.
# live 1.4.0
* Variable selection is now based on LASSO as implemented in glmnet package.
* Updated documentation and vignette.
# live 1.3.3
* `add_predictions` also returns black box model object (`model` element).
# live 1.3.2
* Hyperparameters can be also passed to `add_predictions` function.
# live 1.3.1
* `fit_explanation` is now more flexible, can take a list of hyperparameters for a chosen model.
# live 1.3.0
* For classification problems waterfall plots can be drawn on probability or logit scale.
# live 1.2.0
* Now using forestmodel package for better factor handling.
# live 1.1.2
* Date variables will now be hold constant while performing local exploration.
* Improved performance.
# live 1.1.1
* `add_predictions` improved to handle more learners (for example ranger).
# live 1.1.0
* Added a `NEWS.md` file to track changes to the package.
* `sample\_locally` uses data.table for faster local exploration.
# live 1.0.0
* Cheatsheet added.
* First package release.