Conformal Prediction for Reliable Machine Learning

Language: English

Published by Morgan Kaufmann, 2014

0123985374 / 9780123985378

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This item is printed on demand - it takes 3-4 days longer - Neuware -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 apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. Englisch.

Seller Inventory # 9780123985378

Title
Conformal Prediction for Reliable Machine Learning
Author
Vineeth Balasubramanian
Publisher
Morgan Kaufmann
Publication year
2014
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
0123985374
ISBN 13
9780123985378
Item weight
672 grams
Dimensions
235x191x15 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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BuchWeltWeit Ludwig Meier e.K.

Germany