Feature and Dimensionality Reduction for Clustering with Deep Learning : Unsupervised and Semi-Supervised Learning - Frederic Ros

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Feature and Dimensionality Reduction for Clustering with Deep Learning

By: Frederic Ros, Rabia Riad

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Hardcover | 3 January 2024

At a Glance

Hardcover
282 Pages

Dimensions(cm)
23.5 x 15.5 x 1.75

Hardcover

RRP $199.00

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This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by "family" to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.

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