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New Directions in Behavioral Biometrics by Khalid Saeed; ISBN 9781498784627
A First Course in Machine Learning, Second Edition by Simon Rogers and Mark Girolami; ISBN 9781498738484
Machine Learning: Algorithms and Applications by Mohssen Mohammed, Muhammad Badruddin Khan, and Eihab Bashier Mohammed Bashier; ISBN 9781498705387
Anti-Spam Techniques Based on Artificial Immune System by Ying Tan; ISBN 9781498725187
The Cognitive Early Warning Predictive System Using the Smart Vaccine: The New Digital Immunity Paradigm for Smart Cities and Critical Infrastructure by Rocky Termanini; ISBN 9781498726511

What Is Uncertainty in Machine Learning?

Xizhao Wang and Junhai Zhai

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Uncertainty is a common phenomenon in machine learning, which can be found in every phase of learning, such as data preprocessing, algorithm design, and model selection. The representation, measurement, and handling of uncertainty have a significant impact on the performance of a learning system. There are four common uncertainties in machine learning. This chapter from Learning with Uncertainty introduces the first three kinds of uncertainty, briefly lists the fourth uncertainty, and gives a short discussion about the relationships among the four uncertainties.


About the Book

Learning with Uncertainty
 by Xizhao Wang and Junhai Zhai; ISBN 9781498724128 From Learning with Uncertainty by Xizhao Wang and Junhai Zhai; ISBN 978-1-4987-2412-8. CRC Press, 2016.


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