Is there a way to make partial dependence plots for random forest with multiple classification in Python (using scikit-learn)?
You have to specify the class for which you want to plot the partial dependencies. This is done by the parameter "target" in the plot_partial_dependence function
For example, if you have three target classes "low", "medium", "high", you would say plot_partial_dependence(estimator, ..., target='high').
However, I'm still trying to find some answers regarding the interpretations of partial dependency plots for multi-class-classifiers. If you have some information, let me know.
Is there a way to make partial dependence plots for the random forest with multiple classification in Python (using scikit-learn)?
I'm raising a separate question about this because I'm not sure if such a function exists in scikit-learn. I've seen a few examples in R already. If the function doesn't exist, I will make the request in scikit-learn github, but just want to double-check with the community before making the request.
If you know of any other Python package other than scikit learn that could conduct the plot, please let me know. Thanks.