Advances in Feature Selection for Data and Pattern Recognition (Hardcover)

Beata Zielosko

ISBN 10: 3319675877 / ISBN 13: 9783319675879

Published by Springer International Publishing AG, Cham, 2017

About this Item

Hardcover. This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances.The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.Divided into four parts nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professorsand practitioners. This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances.The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9783319675879

Bibliographic Details

• Title: Advances in Feature Selection for Data and Pattern Recognition (Hardcover)
• Publisher: Springer International Publishing AG, Cham
• Publication Date: 2017
• Language: English
• ISBN 10: 3319675877
• ISBN 13: 9783319675879
• Binding: Hardcover
• Edition: 1st Edition
• Condition: new

About this title

Synopsis

This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances.

The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.

Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professorsand practitioners.