LEADER 04164nam 22006615 450 001 9910299886903321 005 20200629215301.0 010 $a3-319-67588-5 024 7 $a10.1007/978-3-319-67588-6 035 $a(CKB)4100000001041585 035 $a(DE-He213)978-3-319-67588-6 035 $a(MiAaPQ)EBC5149969 035 $z(PPN)258859105 035 $a(PPN)221252673 035 $a(EXLCZ)994100000001041585 100 $a20171116d2018 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Feature Selection for Data and Pattern Recognition /$fedited by Urszula Sta?czyk, Beata Zielosko, Lakhmi C. Jain 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XVIII, 328 p. 37 illus., 20 illus. in color.) 225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v138 311 $a3-319-67587-7 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aAn 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. 330 $aThis book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts ? nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners. 410 0$aIntelligent Systems Reference Library,$x1868-4394 ;$v138 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aPattern recognition 606 $aData mining 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aPattern recognition. 615 0$aData mining. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aData Mining and Knowledge Discovery. 676 $a006.4 702 $aSta?czyk$b Urszula$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZielosko$b Beata$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJain$b Lakhmi C$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299886903321 996 $aAdvances in Feature Selection for Data and Pattern Recognition$92537862 997 $aUNINA