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Best Practices in Forecast Evaluation by Pablo Ernesto Vigneaux Wilton is a document available to read on EtoBox.

This document discusses the challenges and best practices in forecast evaluation for machine learning and deep learning techniques applied to time series data. It highlights common pitfalls faced by data scientists due to a lack of familiarity with traditional forecasting methods and emphasizes the importance of proper evaluation practices to avoid misleading conclusions. The authors provide guidelines on data partitioning, error calculation, and selecting appropriate error measures tailored to the characte

Author
Pablo Ernesto Vigneaux Wilton
Language
EN