For binary classification, I am getting only a unicolor feature importance plot (i.e., the two classes do not appear individually).
However, for multiclass, I am getting feature importance in different colors. Can someone please explain why I am not getting the same for binary classification?
thank you for the answer. But I am doing it for two classes (i.e., binary classification). I have also seen people plotting for two classes (please see the figure below). I want to do the same in my case. In binary classification, the "shap_values = explainer.shap_values(X)" only produces one array in binary classification. However, it produces three arrays in multi-class, as I have three.