Open jmaspons opened 2 years ago
Hi @jmaspons, thanks for this contribution. I will try to review it next week.
Hello,
You can find a test script with dummy data at https://gist.github.com/jmaspons/0199ef922571bafe5eaac1a056963a83 (it requires keras, abind, DALEX and data.table packages). The patch implements feature_importance for models with more than one input datasets as 2D and 3D arrays. It can be useful for time series data (3D to a RNN) with some static variables (2D). DALEX::explainer doesn't support this kind of data input, so no changes to feature_importance.explainer
The feature_importance.default and feature_importance.multiinput
In order to add tests, do you think it's acceptable to add all the dependencies or skip some by saving some data in the package?
For starters, we should use underscore notation for function parameters instead of camelCase, e.g. perm_dim
.
In order to add tests, do you think it's acceptable to add all the dependencies or skip some by saving some data in the package?
All such dependencies should be added to suggests
; we wouldn't want more dependencies in imports
. It would be nice to have some tests; they can run on generated data.
let's not have data.table
and keras
as dependencies
let's not have
data.table
andkeras
as dependencies
I'll find alternatives implementations for the data.table
part. For the keras
tests, is it ok to make it conditional and add keras
in the suggested packages section?
we are trying to have DALEX
as light as possible and keras
is quite heavy package
so maybe a valid solution would be to move this function to DALEXtra
?
(it has some heavy dependencies)
Datasets can be 2d or 3d arrays