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CRC Press - Learning with Uncertainty Machine Learning Book

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Description

Master the complexities of machine learning in unpredictable environments with Learning with Uncertainty by CRC Press. This comprehensive text provides a deep dive into how randomness, roughness, fuzziness, and non-specificity affect data models and learning processes. Designed for those studying econometrics and advanced machine learning, the book explores how to represent and manage uncertainty within various computational frameworks. You will explore practical applications including decision tree learning and clustering methods specifically designed for uncertain environments. By studying active learning based on uncertainty criteria and ensemble learning frameworks, readers gain the tools necessary to handle real-world data challenges. This book serves as a detailed guide for understanding the influence of uncertainty on performance and how to build more robust models in unpredictable scenarios.

Key Features

Covers decision tree learning techniques specifically designed to handle uncertainty in data sets.

Explores clustering methods that function effectively within uncertain environments.

Provides insights into active learning approaches based on specific uncertainty criteria.

Discusses ensemble learning methods within a specialized framework of uncertainty.

Introduces fundamental concepts including randomness, roughness, fuzziness, and non-specificity.

Analyzes how uncertainty representation affects the overall performance of learning models.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
16 September 2016
Listed Since
11 January 2016

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