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000851401 020__ $$a9783319981406$$q(electronic book)
000851401 020__ $$a3319981404$$q(electronic book)
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000851401 08204 $$a006.3/12$$223
000851401 1001_ $$aVentura, S.$$q(Sebastian),$$eauthor.
000851401 24510 $$aSupervised Descriptive Pattern Mining /$$cSebastian Ventura, Jose Maria Luna.
000851401 264_1 $$aCham, Switzerland :$$bSpringer Nature,$$c2018.
000851401 300__ $$a1 online resource.
000851401 336__ $$atext$$btxt$$2rdacontent
000851401 337__ $$acomputer$$bc$$2rdamedia
000851401 338__ $$aonline resource$$bcr$$2rdacarrier
000851401 5050_ $$aIntro; Acknowledgments; Contents; 1 Introduction to Supervised Descriptive Pattern Mining; 1.1 Patterns in Data Analysis; 1.2 Pattern Mining: Types of Patterns and Advanced Data Types; 1.2.1 Frequent/Infrequent Patterns; 1.2.2 Positive/Negative Patterns; 1.2.3 Maximal/Closed/Colossal Patterns; 1.2.4 Condensed Patterns; 1.2.5 Patterns on Advanced Data Types; 1.2.5.1 Data Streams; 1.2.5.2 Sequential Data; 1.2.5.3 Spatiotemporal Data; 1.2.5.4 Graphs; 1.2.5.5 High Utility Data; 1.2.5.6 Uncertain Data; 1.2.5.7 Multiple-Instance Data; 1.3 Supervised Descriptive Patterns; 1.3.1 Contrast Sets
000851401 5058_ $$a1.3.2 Emerging Patterns1.3.3 Subgroup Discovery; 1.3.4 Class Association Rules; 1.3.5 Exceptional Models; 1.3.6 Other Forms of Supervised Descriptive Patterns; 1.4 Scalability Issues; 1.4.1 Heuristic Approaches; 1.4.2 New Data Structures; 1.4.3 Parallel Computing; 1.4.4 MapReduce Framework; References; 2 Contrast Sets; 2.1 Introduction; 2.2 Task Definition; 2.2.1 Quality Measures; 2.2.2 Tree Structures; 2.2.2.1 Frequent Tree Ordering; 2.2.2.2 Difference Ordering; 2.2.2.3 Hybrid Ordering; 2.3 Algorithms for Mining Contrast Sets; 2.3.1 STUCCO; 2.3.2 CIGAR; 2.3.3 CSM-SD
000851401 5058_ $$a2.3.4 Additional ApproachesReferences; 3 Emerging Patterns; 3.1 Introduction; 3.2 Task Definition; 3.2.1 Problem Decomposition; 3.2.2 Types of Emerging Patterns; 3.3 Algorithms for Mining Emerging Patterns; 3.3.1 Border-Based Algorithms; 3.3.2 Constraint-Based Algorithms; 3.3.3 Tree-Based Algorithms; 3.3.4 Evolutionary Fuzzy System-Based Algorithms; References; 4 Subgroup Discovery; 4.1 Introduction; 4.2 Task Definition; 4.2.1 Quality Measures; 4.2.1.1 Discrete Target Variables; 4.2.1.2 Numerical Target Variables; 4.2.2 Unifying Related Tasks; 4.3 Algorithms for Subgroup Discovery
000851401 5058_ $$a4.3.1 Extensions of Classification Algorithms4.3.2 Extensions of Association Rule Mining Algorithms; 4.3.3 Evolutionary Algorithms; 4.3.4 Big Data Approaches; References; 5 Class Association Rules; 5.1 Introduction; 5.2 Task Definition; 5.2.1 Quality Measures; 5.2.2 Class Association Rules for Descriptive Analysis; 5.2.3 Class Association Rules for Predictive Analysis; 5.2.4 Related Tasks; 5.3 Algorithms for Class Association Rules; 5.3.1 Algorithms for Descriptive Analysis; 5.3.2 Algorithms for Predictive Analysis; References; 6 Exceptional Models; 6.1 Introduction; 6.2 Task Definition
000851401 5058_ $$a6.2.1 Original Model Classes6.2.1.1 Correlation Models; 6.2.1.2 Regression Models; 6.2.1.3 Classification Models; 6.2.2 Rank Correlation Model Class; 6.2.3 Related Tasks; 6.3 Algorithms for Mining Exceptional Models; 6.3.1 Exceptional Model Mining; 6.3.2 Exceptional Preference Mining; 6.3.3 Exceptional Relationship Mining; References; 7 Other Forms of Supervised Descriptive Pattern Mining; 7.1 Introduction; 7.2 Additional Tasks; 7.2.1 Closed Sets for Labeled Data; 7.2.2 Bump Hunting; 7.2.3 Impact Rules; 7.2.4 Discrimination Discovery; 7.2.5 Describing Black Box Models; 7.2.6 Change Mining
000851401 506__ $$aAccess limited to authorized users.
000851401 588__ $$aOnline resource; title from PDF title page (viewed October 10, 2018).
000851401 650_0 $$aData mining.
000851401 650_0 $$aPattern recognition systems.
000851401 7001_ $$aLuna, José María,$$eauthor.
000851401 852__ $$bebk
000851401 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-98140-6$$zOnline Access$$91397441.1
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000851401 980__ $$aBIB
000851401 982__ $$aEbook
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