Black-box explainer for time series forecasting
AssigneeInternational Business Machines Corporation
InventorsVikas C. Raykar, Sumanta Mukherjee, Nupur Aggarwal, Bhanukiran Vinzamuri, Arindam Jati
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AssigneeInternational Business Machines Corporation
InventorsVikas C. Raykar, Sumanta Mukherjee, Nupur Aggarwal, Bhanukiran Vinzamuri, Arindam Jati
Estimating the term…
A method, system, and computer program product for an interpretable, feature-based post-hoc black box explainer for univariate time series forecasters are provided. The method receives a set of time series forecasting predictions. The set of time series forecasting predictions are generated from a set of black-box models trained with an initial data set. The method generates a set of features based on at least a portion of the initial data set. A set of surrogate models are trained based on the set of time series forecasting predictions and at least a portion of the set of features. A subset of surrogate models is selected. Based on the subset of surrogate models, the method generates one or more explanation outputs for time series forecasting predictions of the set of black-box models.
A computer-implemented method, comprising:
A system, comprising:
A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being executable by one or more processors to cause the one or more processors to perform operations comprising:
Dependencies are inferred from the claim text.