For this line of code shap.summary_plot(shap_values, X_val_vec, feature_names=feature_names), my plot is coming out looking like this.
shap summary plot
I am unsure what to change to make it come out correctly.
X_val_vec is testing textual data that has been vectorized using tfidf. feature_names is equal to 'vectorizer.get_features_names_out()' Using a random forest model. This is my code for making the explainer object - 'explainer = shap.Explainer(model, X_train_vec, feature_names=feature_names, check_additivity = False, algorithm = "tree")' X_train_vec is text data used for training that is vectorized using tfidf.
I have been able to get the waterfall plot to work, but the summary plot and a few others are not coming out right.