# 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

# 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.