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Working Papers

 
 Title

Customized forecasting with Adaptive Ensemble Generator

 Authors

Waychal, Nachiketas; Laha, Arnab Kumar; Sinha, Ankur

 Publication Date

30-Jun-2022

 Year

2022

  Publication Code

WP 2022-06-04

 Abstract

In this paper, we propose a new approach for generating a customized forecast ensemble that considers the user's preferences across multiple criteria. The proposed algorithm takes inputs from the user and computes a set of optimal weights assignable to the n chosen criteria. Using these weights, we define a metric called the Multi-Criteria Value, which is maximized to obtain the customized ensemble. This algorithm is called Adaptive Ensemble Generator since it incorporates m distinct forecasting methods and n evaluation criteria. We demonstrate this algorithm customized for four different users (three real-life users and one designed user) on a large database.

 

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