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Home Page: https://dalex.drwhy.ai
License: Creative Commons Attribution Share Alike 4.0 International
Documentation for the DALEX project
Home Page: https://dalex.drwhy.ai
License: Creative Commons Attribution Share Alike 4.0 International
Hello,
I'm trying the arena service for my model and data,
I saw all the possibilities that the web page gives, it is really useful!
But I found a problem when trying to check the shap - breakdown - ceteris values on a custom observation. I'm changing it in the Observation Details tab, where an slider appears to change the values of the variables.
The value print on the terminal is:
ValueError: Input X contains NaN.
RandomForestClassifier does not accept missing values encoded as NaN natively. For supervised learning, you might want to consider sklearn.ensemble.HistGradientBoostingClassifier and Regressor which accept missing values encoded as NaNs natively. Alternatively, it is possible to preprocess the data, for instance by using an imputer transformer in a pipeline or drop samples with missing values. See https://scikit-learn.org/stable/modules/impute.html You can find a list of all estimators that handle NaN values at the following page: https://scikit-learn.org/stable/modules/impute.html#estimators-that-handle-nan-values
Any idea?
Thanks!
PD: I'm using a random forest model and the titanic dataset with a few modifications.
produce new images where appropriate https://python.drwhy.ai
and maybe change layout for two rows instead of one
and i honestly don't know how to fix it
..and add vignettes: teaching2
, BreakDown/LIME/Shapley
comparison
two .md
files
In fairness notebook numerical columns were omitted by the model. It should be fixed.
v1.4.0
please
update dalex-fairness vignette
dalex-fairness.ipynb
dalex-fairness.ipynb
file as a source to python-dalex-fairness2.html
mentions ModelOriented/DALEX#432
Both of these could use some help <3
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