TsSHAP: Robust model agnostic feature-based explainability for time series forecasting

no code implementations • 22 Mar 2023 • Vikas C. Raykar, Arindam Jati, Sumanta Mukherjee, Nupur Aggarwal, Kanthi Sarpatwar, Giridhar Ganapavarapu, Roman Vaculin

The explanations are in terms of the SHAP values obtained by applying the TreeSHAP algorithm on a surrogate model that learns a mapping between the interpretable feature space and the forecast of the black-box model.

Time Series Time Series Forecasting

Hyper-local sustainable assortment planning

no code implementations • 27 Jul 2020 • Nupur Aggarwal, Abhishek Bansal, Kushagra Manglik, Kedar Kulkarni, Vikas Raykar

Assortment planning, an important seasonal activity for any retailer, involves choosing the right subset of products to stock in each store. While existing approaches only maximize the expected revenue, we propose including the environmental impact too, through the Higg Material Sustainability Index.