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You're reading from  Practical Guide to Applied Conformal Prediction in Python

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781805122760
Edition1st Edition
Concepts
Machine Learning
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Author (1)
Valery Manokhin
Valery Manokhin
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Valery Manokhin

Valeriy Manokhin is the leading expert in the field of machine learning and Conformal Prediction. He holds a Ph.D.in Machine Learning from Royal Holloway, University of London. His doctoral work was supervised by the creator of Conformal Prediction, Vladimir Vovk, and focused on developing new methods for quantifying uncertainty in machine learning models. Valeriy has published extensively in leading machine learning journals, and his Ph.D. dissertation 'Machine Learning for Probabilistic Prediction' is read by thousands of people across the world. He is also the creator of "Awesome Conformal Prediction," the most popular resource and GitHub repository for all things Conformal Prediction.
Read more about Valery Manokhin

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Conformal prediction for regression problems

In the preceding chapters, we investigated the numerous advantages that conformal prediction provides. These include the following:

  • Validity and calibration: Conformal prediction maintains its validity and calibration, irrespective of the dataset’s size. This makes it a robust method for prediction across different dataset sizes.
  • Distribution-free nature: One of the significant benefits of conformal prediction is its distribution-free nature. It makes no specific assumptions about the underlying data distribution, making it a flexible and versatile tool for many prediction problems.
  • Compatibility with various predictors: Conformal prediction can seamlessly integrate with any point predictor, irrespective of its nature. This property enhances its adaptability and widens its scope of application in diverse domains.
  • Non-intrusiveness: The conformal prediction framework is non-intrusive, implying that it does not interfere...
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Practical Guide to Applied Conformal Prediction in Python
Published in: Dec 2023Publisher: PacktISBN-13: 9781805122760
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Valery Manokhin

Valeriy Manokhin is the leading expert in the field of machine learning and Conformal Prediction. He holds a Ph.D.in Machine Learning from Royal Holloway, University of London. His doctoral work was supervised by the creator of Conformal Prediction, Vladimir Vovk, and focused on developing new methods for quantifying uncertainty in machine learning models. Valeriy has published extensively in leading machine learning journals, and his Ph.D. dissertation 'Machine Learning for Probabilistic Prediction' is read by thousands of people across the world. He is also the creator of "Awesome Conformal Prediction," the most popular resource and GitHub repository for all things Conformal Prediction.
Read more about Valery Manokhin

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