Advances in Feature Selection for Data and Pattern Recognition

Springer (Verlag)
  • erschienen am 1. September 2018
  • Buch
  • |
  • Softcover
  • |
  • 348 Seiten
978-3-319-88452-3 (ISBN)
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.
Softcover reprint of the original 1st ed. 2018
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
  • 20 farbige Abbildungen, 100 farbige Tabellen, 17 s/w Abbildungen
  • |
  • 100 Tables, color; 20 Illustrations, color; 17 Illustrations, black and white; XVIII, 328 p. 37 illus., 20 illus. in color.
  • Höhe: 235 mm
  • |
  • Breite: 155 mm
  • |
  • Dicke: 18 mm
  • 528 gr
978-3-319-88452-3 (9783319884523)
weitere Ausgaben werden ermittelt
An Introduction.- Attribute Selection Based on Reduction of Numerical Attribute During Discretization.- Improving Bagging Ensembles for Class Imbalanced Data by Active Learning.- Optimization of Decision Rules Relative to Length Based on Modi?ed Dynamic Programming Approach.- Ranking-Based Rule Classi?er Optimisation.- Attribute Selection in a Dispersed Decision-Making System.- Feature Selection Approach for Rule-based Knowledge Bases.- Feature Selection with a Genetic Algorithm for Classi?cation of Brain Imaging Data.

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