000 03140nam a22005295i 4500
001 978-1-4939-0539-3
003 DE-He213
005 20200420220226.0
007 cr nn 008mamaa
008 140214s2014 xxu| s |||| 0|eng d
020 _a9781493905393
_9978-1-4939-0539-3
024 7 _a10.1007/978-1-4939-0539-3
_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 _aDahan, Haim.
_eauthor.
245 1 0 _aProactive Data Mining with Decision Trees
_h[electronic resource] /
_cby Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aX, 88 p. 20 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
505 0 _aIntroduction -- Proactive Data Mining: A General Approach -- Proactive Data Mining Using Decision Trees -- Proactive Data Mining in the Real World: Case Studies -- Sensitivity Analysis of Proactive Data Mining -- Conclusions.
520 _aThis book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.
650 0 _aComputer science.
650 0 _aData mining.
650 0 _aInformation storage and retrieval.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aInformation Systems Applications (incl. Internet).
700 1 _aCohen, Shahar.
_eauthor.
700 1 _aRokach, Lior.
_eauthor.
700 1 _aMaimon, Oded.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781493905386
830 0 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-0539-3
912 _aZDB-2-SCS
942 _cEBK
999 _c52231
_d52231