I tried the python version of dalex with a multiregression model and it gave an error. (See below)
Is there any way around it ?
If i understand correctly iBreakdown/pyBreakdown can deal with multiple classes for classification which are also probabilities organized in multiple columns/arrays so this should be quite similar. Would be great if this would be enabled.
The SHAP package also supports Shap values for the multirgression case.

Can i call ibreakdown directly from dalex, without generating an explainer object ? The ibreakdown for Python has not been updated in a while but the new Python Dalex seems quite active.

decision tree for multioutput regression

import dalex as dx
from sklearn.datasets import make_regression
from sklearn.tree import DecisionTreeRegressor

create datasets

X, y = make_regression(n_samples=1000, n_features=10, n_informative=5, n_targets=2, random_state=1, noise=0.5)

define model

model = DecisionTreeRegressor()

model.fit(X,y)

dx.Explainer(model,X,y)

data is converted to pd.DataFrame, columns are set as string numbers
-> data : 1000 rows 10 cols
Traceback (most recent call last):

File "", line 11, in
dx.Explainer(model,X,y)

File "C:\Users\Thomas Wolf\anaconda3\envs\my-rdkit-env\lib\site-packages\dalex_explainer\object.py", line 131, in init
y = check_y(y, data, verbose)

File "C:\Users\Thomas Wolf\anaconda3\envs\my-rdkit-env\lib\site-packages\dalex_explainer\checks.py", line 52, in check_y
raise ValueError("y must have only one dimension")

ValueError: y must have only one dimension