000 03285nam a22005175i 4500
001 978-3-319-73040-0
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008 180118s2018 sz | s |||| 0|eng d
020 _a9783319730400
_9978-3-319-73040-0
024 7 _a10.1007/978-3-319-73040-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aKovalerchuk, Boris.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_955860
245 1 0 _aVisual Knowledge Discovery and Machine Learning
_h[electronic resource] /
_cby Boris Kovalerchuk.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXXI, 317 p. 274 illus., 263 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 ;
_v144
505 0 _aMotivation, Problems and Approach -- General Line Coordinates (GLC) -- Theoretical and Mathematical Basis of GLC -- Adjustable GLCs for decreasing occlusion and pattern simplification -- GLC Case Studies -- Discovering visual features and shape perception capabilities in GLC -- Interactive Visual Classification, Clustering and Dimension Reduction with GLC-L -- Knowledge Discovery and Machine Learning for Investment Strategy with CPC.
520 _aThis book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
710 2 _aSpringerLink (Online service)
_955861
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319730394
776 0 8 _iPrinted edition:
_z9783319730417
776 0 8 _iPrinted edition:
_z9783319892306
830 0 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v144
_955862
856 4 0 _uhttps://doi.org/10.1007/978-3-319-73040-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79637
_d79637