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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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The validity of probabilistic predictors

We start by summarizing the reasons why unbiased point prediction models are important across various domains and applications:

  • Accuracy and reliability: An unbiased model ensures that the predictions it generates are accurate and reliable on average, meaning that the model is neither systematically overestimating nor underestimating the true values. This accuracy is crucial for making well-informed decisions, minimizing risks, and improving the overall performance of a system.
  • Trust and credibility: Unbiased prediction models help build trust and credibility among stakeholders, as they provide a reliable basis for decision-making. Users can have more confidence in the outputs generated by an unbiased model, knowing that it is not skewed or favoring any specific outcome.
  • Fairness and equity: In some applications, such as finance, healthcare, and human resources, unbiased models are essential to ensure fairness and equity among...
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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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