X = df.copy()
# Save and drop labels
y = df['class']
X = X.drop('class', axis=1)
cat_features = list(range(0, X.shape[1]))
model = CatBoostClassifier(iterations=2000, learning_rate=0.1, random_seed=12)
model.fit(X, y, verbose=False, plot=False)
explainer = shap.Explainer(model)
shap_values = explainer(X)
shap.force_plot(explainer.expected_value, shap_values[0:5,:],X.iloc[0:5,:], plot_cmap="DrDb")
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-170-ba1eca12b9ed> in <module>
----> 1 shap.force_plot(10, shap_values[0:5,:],X.iloc[0:5,:], plot_cmap="DrDb")
~\anaconda3\lib\site-packages\shap\plots\_force.py in force(base_value, shap_values, features, feature_names, out_names, link, plot_cmap, matplotlib, show, figsize, ordering_keys, ordering_keys_time_format, text_rotation, contribution_threshold)
101
102 if type(shap_values) != np.ndarray:
--> 103 return visualize(shap_values)
104
105 # convert from a DataFrame or other types
~\anaconda3\lib\site-packages\shap\plots\_force.py in visualize(e, plot_cmap, matplotlib, figsize, show, ordering_keys, ordering_keys_time_format, text_rotation, min_perc)
343 return AdditiveForceArrayVisualizer(e, plot_cmap=plot_cmap, ordering_keys=ordering_keys, ordering_keys_time_format=ordering_keys_time_format)
344 else:
--> 345 assert False, "visualize() can only display Explanation objects (or arrays of them)!"
346
347 class BaseVisualizer:
AssertionError: visualize() can only display Explanation objects (or arrays of them)!
Was trying to plot with shap and my data, but got a mistake and I actually don't understand why. Haven't found anything about this. Please explain how to avoid this error?
explainer.expected_value
-5.842052267820879
You should change the last line to this : shap.force_plot(explainer.expected_value, shap_values.values[0:5,:],X.iloc[0:5,:], plot_cmap="DrDb")
by calling shap_values.values instead of just shap_values, because shap_values holds the shapley values, the base_values and the data . I had the same problem until I inspected the variable.