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Advances in Feature Selection for Data and Pattern Recognition

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances in Feature Selection for Data and Pattern Recognition/ edited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain.
其他作者:	Stańczyk, Urszula.
面頁冊數:	XVIII, 328 p. 37 illus., 20 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-319-67588-6
ISBN:	9783319675886

Advances in Feature Selection for Data and Pattern Recognition
Advances in Feature Selection for Data and Pattern Recognition[electronic resource] /edited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain. - 1st ed. 2018. - XVIII, 328 p. 37 illus., 20 illus. in color.online resource. - Intelligent Systems Reference Library,1381868-4394 ;. - Intelligent Systems Reference Library,67.

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.

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.

ISBN: 9783319675886

Standard No.: 10.1007/978-3-319-67588-6doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advances in Feature Selection for Data and Pattern Recognition
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