Contents
How is Shap values calculated?
The idea is that: the sum of the weights of all the marginal contributions to 1-feature-models should equal the sum of the weights of all the marginal contributions to 2-feature-models and so on… In other words, the sum of all the weights on the same “row” should equal the sum of all the weights on any other “row”.
What is Shap value machine learning?
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions (see papers for details and citations).
How are Shap values computed in a model?
SHAP values are computed in a way that attempts to isolate away of correlation and interaction, as well. import shap explainer = shap.TreeExplainer(model) shap_values = explainer.shap_values(X, y=y.values) SHAP values are also computed for every input, not the model as a whole, so these explanations are available for each input individually.
How are Shap values used in machine learning?
These values are readily interpretable, as each value is a feature’s effect on the prediction, in its units. A SHAP value of 1000 here means “explained +$1,000 of predicted salary”. SHAP values are computed in a way that attempts to isolate away of correlation and interaction, as well.
How are Shap and shapely values used in game theory?
SHAP and Shapely Values are based on the foundation of Game Theory. Shapely values guarantee that the prediction is fairly distributed across different features (variables). SHAP can compute the global interpretation by computing the Shapely values for a whole dataset and combine them.
How to do a variable importance plot in Shap?
A variable importance plot lists the most significant variables in descending order. The top variables contribute more to the model than the bottom ones and thus have high predictive power. Readers may want to output any of the summary plots. Although the SHAP does not have built-in functions, you can output the plot by using matplotlib: