Webb11 mars 2024 · SHAP values are additive by construction (to be precise SHapley Additive exPlanations are average marginal contributions over all possible feature coalitions) exp … Webb2 mars 2024 · the force plot(s) explaining the model’s output for that observation. I hope you found this helpful and are able to apply something you’ve learned to your own work! …
【可解释性机器学习】详解Python的可解释机器学习库:SHAP – …
Webb27 dec. 2024 · Apart from @Sarah answer, the scale of SHAP values based on the discussion in this issue could transform via inverse_transform () as follows: x_scaler.inverse_transform (shap_values) 3. Based on Github the base value: The average model output over the training dataset has been passed Model Base value = 0.6427 Webb17 jan. 2024 · The force plot is another way to see the effect each feature has on the prediction, for a given observation. In this plot the positive SHAP values are displayed on … haufe governance
shap.force_plot — SHAP latest documentation - Read the Docs
WebbIf you have the appropriate dependencies installed (i.e., reticulate and shap) then you can utilize shap ’s additive force layout (Lundberg et al. 2024) to visualize fastshap ’s prediction explanations; see ?fastshap::force_plot for details. # Visualize first explanation force_plot (object = ex [1L, ], feature_values = X [1L, ], display ... Webbshap.plots.force(base_value, shap_values=None, features=None, feature_names=None, out_names=None, link='identity', plot_cmap='RdBu', matplotlib=False, show=True, figsize=(20, 3), ordering_keys=None, ordering_keys_time_format=None, text_rotation=0, contribution_threshold=0.05) Visualize the given SHAP values with an additive force … Webb20 mars 2024 · 1 Answer Sorted by: 8 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 . boox note air uk