Advances in Feature Selection for Data and Pattern Recognition

Urszula Sta¿czyk

ISBN 10: 3319675877 / ISBN 13: 9783319675879

Verlag: Springer International Publishing, 2017

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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.

Bestandsnummer des Verkäufers 9783319675879

Bibliografische Details

• Titel: Advances in Feature Selection for Data and Pattern Recognition
• Verlag: Springer International Publishing
• Erscheinungsjahr: 2017
• Sprache: Englisch
• ISBN-10: 3319675877
• ISBN-13: 9783319675879
• Einband: Buch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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, professors and practitioners.