Whitepaper
September 25, 2024

Explainable AI for Forecasts you can Trust

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Read this whitepaper to learn how to provide greater transparency and insight into model behavior by understanding the processes and methods that allow human users to comprehend and trust the results and outputs created by machine learning algorithms.

In this paper, we'll dive into the following concepts:

  • Why explainability matters
  • What explainable AI (XAI) is
  • How to use advanced time series techniques to deliver explainable forecasts
  • Ikigai's unique three-part approach to explainable forecasting
  • Using Time2Vec for 'similar trend' based validation
  • How explainable AI improves demand forecasting

Author

Alex Gammelgard
Director of Product Marketing
Ikigai

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