04164nam 22006615 450 991029988690332120200629215301.03-319-67588-510.1007/978-3-319-67588-6(CKB)4100000001041585(DE-He213)978-3-319-67588-6(MiAaPQ)EBC5149969(PPN)258859105(PPN)221252673(EXLCZ)99410000000104158520171116d2018 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierAdvances in Feature Selection for Data and Pattern Recognition /edited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (XVIII, 328 p. 37 illus., 20 illus. in color.)Intelligent Systems Reference Library,1868-4394 ;1383-319-67587-7 Includes bibliographical references at the end of each chapters and index.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.Intelligent Systems Reference Library,1868-4394 ;138Computational intelligenceArtificial intelligencePattern recognitionData miningComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XData Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Computational intelligence.Artificial intelligence.Pattern recognition.Data mining.Computational Intelligence.Artificial Intelligence.Pattern Recognition.Data Mining and Knowledge Discovery.006.4Stańczyk Urszulaedthttp://id.loc.gov/vocabulary/relators/edtZielosko Beataedthttp://id.loc.gov/vocabulary/relators/edtJain Lakhmi Cedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910299886903321Advances in Feature Selection for Data and Pattern Recognition2537862UNINA