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001 978-3-319-67588-6
003 DE-He213
005 20220801215244.0
007 cr nn 008mamaa
008 171116s2018 sz | s |||| 0|eng d
020 _a9783319675886
_9978-3-319-67588-6
024 7 _a10.1007/978-3-319-67588-6
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aAdvances in Feature Selection for Data and Pattern Recognition
_h[electronic resource] /
_cedited by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVIII, 328 p. 37 illus., 20 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v138
505 0 _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 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.
520 _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.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 0 _aPattern recognition systems.
_93953
650 0 _aData mining.
_93907
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aData Mining and Knowledge Discovery.
_943271
700 1 _aStańczyk, Urszula.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943272
700 1 _aZielosko, Beata.
_eeditor.
_0(orcid)0000-0003-3788-1094
_1https://orcid.org/0000-0003-3788-1094
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943273
700 1 _aJain, Lakhmi C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943274
710 2 _aSpringerLink (Online service)
_943275
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319675879
776 0 8 _iPrinted edition:
_z9783319675893
776 0 8 _iPrinted edition:
_z9783319884523
830 0 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v138
_943276
856 4 0 _uhttps://doi.org/10.1007/978-3-319-67588-6
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c77286
_d77286