000 03248nam a22005415i 4500
001 978-1-4471-6407-4
003 DE-He213
005 20200421112231.0
007 cr nn 008mamaa
008 140327s2014 xxk| s |||| 0|eng d
020 _a9781447164074
_9978-1-4471-6407-4
024 7 _a10.1007/978-1-4471-6407-4
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
082 0 4 _a006.312
_223
100 1 _aSimovici, Dan A.
_eauthor.
245 1 0 _aMathematical Tools for Data Mining
_h[electronic resource] :
_bSet Theory, Partial Orders, Combinatorics /
_cby Dan A. Simovici, Chabane Djeraba.
250 _a2nd ed. 2014.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2014.
300 _aXI, 831 p. 93 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvanced Information and Knowledge Processing,
_x1610-3947
505 0 _aSets, Relations and Functions -- Partially Ordered Sets -- Combinatorics -- Topologies and Measures -- Linear Spaces -- Norms and Inner Products -- Spectral Properties of Matrices -- Metric Spaces Topologies and Measures -- Convex Sets and Convex Functions -- Graphs and Matrices -- Lattices and Boolean Algebras -- Applications to Databases and Data Mining -- Frequent Item Sets and Association Rules -- Special Metrics -- Dimensions of Metric Spaces -- Clustering.
520 _aData mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book.  Topics include partially ordered sets, combinatorics,  general topology, metric spaces, linear spaces, graph theory.  To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc.  The book is intended as a reference for researchers and graduate students.  The current edition is a significant expansion of the first edition.  We strived to make the book self-contained, and only a general knowledge of mathematics is required.  More than 700 exercises are included and they form an integral part of the material.  Many exercises are in reality supplemental material and their solutions are included.
650 0 _aComputer science.
650 0 _aComputer science
_xMathematics.
650 0 _aData mining.
650 0 _aComputer mathematics.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aMathematics of Computing.
650 2 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aComputational Mathematics and Numerical Analysis.
700 1 _aDjeraba, Chabane.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447164067
830 0 _aAdvanced Information and Knowledge Processing,
_x1610-3947
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-6407-4
912 _aZDB-2-SCS
942 _cEBK
999 _c57989
_d57989