Vai al contenuto principale della pagina

Advances in Feature Selection for Data and Pattern Recognition / / edited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Titolo: Advances in Feature Selection for Data and Pattern Recognition / / edited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (XVIII, 328 p. 37 illus., 20 illus. in color.)
Disciplina: 006.4
Soggetto topico: Computational intelligence
Artificial intelligence
Pattern recognition
Data mining
Computational Intelligence
Artificial Intelligence
Pattern Recognition
Data Mining and Knowledge Discovery
Persona (resp. second.): StańczykUrszula
ZieloskoBeata
JainLakhmi C
Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
Nota di contenuto: 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 Modified Dynamic Programming Approach -- Ranking-Based Rule Classifier Optimisation -- Attribute Selection in a Dispersed Decision-Making System -- Feature Selection Approach for Rule-based Knowledge Bases -- Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data.
Sommario/riassunto: 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.
Titolo autorizzato: Advances in Feature Selection for Data and Pattern Recognition  Visualizza cluster
ISBN: 3-319-67588-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299886903321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Intelligent Systems Reference Library, . 1868-4394 ; ; 138