[PDF.84mb] Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications
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Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications
From Morgan Kaufmann
[PDF.ko70] Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications
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| #3652522 in Books | 2014-05-13 | 2014-04-29 | Original language:English | PDF # 1 | 9.25 x.73 x7.50l,1.47 | File type: PDF | 334 pages||||"...captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection."--Zentralblatt MATH, Sep-14 |"...the book
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to...
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