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You're reading from  Modern Time Series Forecasting with Python

Product typeBook
Published inNov 2022
PublisherPackt
ISBN-139781803246802
Edition1st Edition
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Manu Joseph
Manu Joseph
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Manu Joseph

Manu Joseph is a self-made data scientist with more than a decade of experience working with many Fortune 500 companies enabling digital and AI transformations, specifically in machine learning-based demand forecasting. He is considered an expert, thought leader, and strong voice in the world of time series forecasting. Currently, Manu leads applied research at Thoucentric, where he advances research by bringing cutting-edge AI technologies to the industry. He is also an active open-source contributor and developed an open-source library—PyTorch Tabular—which makes deep learning for tabular data easy and accessible. Originally from Thiruvananthapuram, India, Manu currently resides in Bengaluru, India, with his wife and son
Read more about Manu Joseph

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How to choose a multi-step forecasting strategy?

Let’s summarize all the different strategies that we learned now in a table:

Figure 17.9 – Multi-step forecasting strategies – a summary

Here, the following applies:

  • S.O: Single output
  • M.O: Multi-output
  • and : Training and inferencing time of a single output model
  • and : Training and inferencing time of a multi-output model (practically, is larger than mostly because multi-output models are typically DL models and their training time is higher than standard ML models)
  • : The horizon
  • , where is the number of blocks in the IBD strategy
  • is some positive real number

The table will help us understand and decide which strategy is better from multiple perspectives:

  • Engineering complexity: Recursive, Joint, RecJoint << IBD << Direct, DirRec << Rectify
  • Training time: Recursive << Joint (typically ) << RecJoint <...
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Modern Time Series Forecasting with Python
Published in: Nov 2022Publisher: PacktISBN-13: 9781803246802

Author (1)

author image
Manu Joseph

Manu Joseph is a self-made data scientist with more than a decade of experience working with many Fortune 500 companies enabling digital and AI transformations, specifically in machine learning-based demand forecasting. He is considered an expert, thought leader, and strong voice in the world of time series forecasting. Currently, Manu leads applied research at Thoucentric, where he advances research by bringing cutting-edge AI technologies to the industry. He is also an active open-source contributor and developed an open-source library—PyTorch Tabular—which makes deep learning for tabular data easy and accessible. Originally from Thiruvananthapuram, India, Manu currently resides in Bengaluru, India, with his wife and son
Read more about Manu Joseph