Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx
Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx
... analyze, and investigate such very large data sets hasgiven rise to the fields of Data Mining (DM) and data warehousing (DW). Withoutclean and correct data the usefulness of Data Mining and data ... examiningdatabases, detecting missing and incorrect data, and correcting errors. Other recentwork relating to data cleansing includes (Bochicchio and Longo, 20 03, Li and Fang,1989). Data Mining ... issue: knowledge bases (Lee et al., 20 01), regular expressionmatches and user-defined constraints (Cadot and di Martion, 20 03), filtering (Sunget al., 20 02) , and others (Feekin, 20 00, Galhardas, 20 01,...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 3 pptx
... and reliability). The internet and intranet fast development in particular pro-O. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_1, ... understanding phenomena from the data, analysis and prediction.The accessibility and abundance of data today makes Knowledge Discovery and Data Mining a matter of considerable importance and necessity. ... means), and analysis of variance (ANOVA). These methods areless associated with Data Mining than their discovery- oriented counterparts, because1 Introduction to Knowledge Discovery and Data Mining...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 25 pptx
... Classification Systems,” Journal of Criminology and Public Policy, 2, No. 2: 21 5 -24 2.Breiman, L., Friedman, J.H., Olshen, R.A., and C.J. Stone, (1984) Classification and Regres-sion Trees. Monterey, Ca: ... (Freund and Schapire, 19 95) and support vector machines (Vapnik, 19 95) aretwo obvious candidates. Moreover, the development of new data mining methodsis progressing very quickly, stimulated in part ... Learning 26 : 123 -140.Breiman, L. (20 00) “Some Infinity Theory for Predictor Ensembles.” Technical Report 52 2 ,Department of Statistics, University of California, Berkeley, California.Breiman, L. (20 01a)...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 38 pptx
... extension to SQL for mining association rules. Data Mining and Knowledge Discovery, 2( 2):1 95 22 4, 1998.T. Mitchell. Generalization as search. Artificial Intelligence, 18 (2) :20 3 22 6, 1980.R. Ng, ... IDEAS’01,pages 322 – 329 , 20 01.C. Bucila, J. E. Gehrke, D. Kifer, and W. White. Dualminer: A dual-pruning algorithm foritemsets with constraints. Data Mining and Knowledge Discovery, 7(4) :24 1 27 2, 20 03.D. ... (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_18, © Springer Science+Business Media, LLC 20 10 17 Constraint-based Data Mining 353 F. Bonchi and C....
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 61 pptx
... %1 10, 326 9,9 72 0 354 99. 72 30K 12s. 2 11, 751 0 10,000 1, 751 1003 7, 923 28 0 7,8 95 78. 95 1 103,331 99,868 0 3,463 99.86300K 56 s. 2 117 ,29 7 0 100,000 17 ,29 7 1003 79,3 72 1 32 0 79 ,24 0 79 .24 1 1,033,7 95 ... for Discovery Science. IEICETransactions on Information and Systems, January 20 00. 58 4 Daniel Barbara and Ping Chen0 50 100 150 20 0 25 0 300 350 4000 50 100 150 20 0 25 0300 350 400Fig. 28 .7. ... 1,033,7 95 998,6 32 0 35, 163 99.863M 485s. 2 1,1 72, 8 95 0 999,999 173,896 99.993 793,310 1,368 0 791,9 42 79.191 10,3 35, 024 9,986,110 22 348,897 99.8630M 4,987s. 2 11, 722 ,887 0 9,999,970 1, 722 ,917...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 74 pptx
... (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_36, © Springer Science+Business Media, LLC 20 10 35 Privacy in Data Mining 7110 20 4060801000 20 406080100Risk/Utility ... MapDRILDistrRemuest1Remuest3JPEG100JPEG010JPEG0 15 JPEG0 95 JPEG 020 MicOI10JPEG 0 25 JPEG030JPEG070MicOI09JPEG0 75 MicOI08JPEG080MicOI07JPEG0 65 JPEG090MicOI06JPEG0 85 MicOI04MicOI 05 MicOI03Adit0.01Adit0. 02 Mic2mul09Rank01JPEG 055 JPEG 050 Mic2mul10JPEG0 35 Mic2mul06Mic2mul 05 Rank 02 JPEG060Mic2mul08Adit0.04Mic2mul07Mic2mul03Mic2mul04JPEG0 45 JPEG040Adit0.06Adit0.08Adit0. 12 Adit0.16Adit0.14Rank03Adit0.1MicZ04Rank04MicZ03Mic3mul09MicZ08Adit0.18MicZ07MicZ 05 Mic3mul10MicZ06MicZ09Mic3mul08MicZ10Mic3mul07MicPCP10MicPCP07MicPCP09Mic3mul03MicPCP 05 MicPCP08Mic3mul04Mic3mul06Mic4mul10Mic3mul 05 MicPCP06Adit0 .2 MicPCP04Mic4mul09Mic4mul08MicPCP03Mic4mul06Mic4mul 05 Mic4mul07Rank06Mic4mul04Mic4mul03Rank 05 Micmul10Micmul07Micmul09Rank08Micmul06Micmul08Micmul 05 Micmul04Micmul03Rank07Rank10Rank09Rank 12 Rank11Rank14Rank13Rank16Rank18Rank 15 Rank17Rank20Rank19+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Fig. ... MapDRILDistrRemuest1Remuest3JPEG100JPEG010JPEG0 15 JPEG0 95 JPEG 020 MicOI10JPEG 0 25 JPEG030JPEG070MicOI09JPEG0 75 MicOI08JPEG080MicOI07JPEG0 65 JPEG090MicOI06JPEG0 85 MicOI04MicOI 05 MicOI03Adit0.01Adit0. 02 Mic2mul09Rank01JPEG 055 JPEG 050 Mic2mul10JPEG0 35 Mic2mul06Mic2mul 05 Rank 02 JPEG060Mic2mul08Adit0.04Mic2mul07Mic2mul03Mic2mul04JPEG0 45 JPEG040Adit0.06Adit0.08Adit0. 12 Adit0.16Adit0.14Rank03Adit0.1MicZ04Rank04MicZ03Mic3mul09MicZ08Adit0.18MicZ07MicZ 05 Mic3mul10MicZ06MicZ09Mic3mul08MicZ10Mic3mul07MicPCP10MicPCP07MicPCP09Mic3mul03MicPCP 05 MicPCP08Mic3mul04Mic3mul06Mic4mul10Mic3mul 05 MicPCP06Adit0 .2 MicPCP04Mic4mul09Mic4mul08MicPCP03Mic4mul06Mic4mul 05 Mic4mul07Rank06Mic4mul04Mic4mul03Rank 05 Micmul10Micmul07Micmul09Rank08Micmul06Micmul08Micmul 05 Micmul04Micmul03Rank07Rank10Rank09Rank 12 Rank11Rank14Rank13Rank16Rank18Rank 15 Rank17Rank20Rank19+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Fig....
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 76 pptx
... on Principles and Practice of Knowledge Discovery in Databases, 20 00.Todorovski, L., Dzeroski, S. Combining Classifiers with Meta Decision Trees. MachineLearning 50 (3), 22 3 - 25 0, 20 03.37 Bias ... Machine Learning, 27 (3): 25 9 -28 6, 1997.Wolpert D. Stacked Generalization. Neural Networks, 5: 24 1 - 25 9, 19 92. 734 Pierre GeurtsToo simple model Too complex modelS1S1 2 2xySSyyxxxyFig. ... left part of Figure 39.1 for twoO. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_37, © Springer Science+Business Media, LLC 20 10...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 93 pptx
... Conference on Knowledge Discovery and Data Mining, pages 30–36. AAAI Press, Menlo Park, CA, 1998.Dehaspe L. and Toivonen H., Discovery of frequent datalog patterns. Data Mining and Knowledge Discovery, ... related topic of using ILP for KDD: AppliedArtificial Intelligence (vol. 12( 5) , 1998), and Data Mining and Knowledge Discovery (vol.3(1), 1999).Many papers related to RDM appear in the ILP ... Blockeel H., Dehaspe L., and Van Laer W., Three Companions for Data Mining in First Order Logic. In (Dˇzeroski and Lavraˇc, 20 01), pages 1 05 139, 20 01.De Raedt L. and Dˇzeroski S., First...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 107 pptx
... commerce, ever-expanding computer systems and mandated record keepingO. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4 _55 , © Springer ... customer and partner relationships and a sustainable competitive advantage. 55 .3 ODM versus Data Mining Data Mining is the process of discovering and interpreting previously unknown patterns indatabases. ... series databases (for reasons discussed below).Below are the major task considered by the time series Data Mining community.O. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook,...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 109 pptx
... the previous section. Figure 56 . 12 illustrates the idea. 56 Mining Time Series Data 10 65 56.4 Time Series RepresentationsAs noted in the previous section, time series datasets are typically very ... Transform(DWT) (Chan and Fu, 1999, Kahveci and Singh, 20 01, Wu et al., 20 00), Piecewise Linear, and Piecewise Constant models (PAA) (Keogh et al., 20 01, Yi and Faloutsos, 20 00), AdaptivePiecewise ... al., 20 04)Chotirat Ann Ratanamahatana et al. 56 Mining Time Series Data 1063time series into a symbolic representation, and encodes the data in a modified suffix tree inwhich the frequency and...
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