Data Mining and Knowledge Discovery Handbook, 2 Edition part 2 pptx
Data Mining and Knowledge Discovery Handbook, 2 Edition part 130 doc
... 703 Regression, 133, 514, 529 , 563 linear, 95, 185, 21 0, 529 , 5 32, 564, 644, 744, 121 2, 127 3 logistic, 97, 21 8, 22 6, 527 , 531, 5 32, 645, 647, 849, 850, 10 32, 1154, 120 0, 120 1, 120 5, 121 2, 127 3 stepwise, 189 Regression,linear, ... 34, 88, 92, 94, 1 12, 135, 151, 163, 795, 798, 881, 899, 907, 961, 9 72, 10 12, 1118, 1198, 127 3 CART, 510 CART (Classification and regressio...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 1 pps
... Rokach Editors Data Mining and Knowledge Discovery Handbook Second Edition 123 Contents 1 Introduction to Knowledge Discovery and Data Mining Oded Maimon, Lior Rokach 1 Part I Preprocessing Methods 2 Data ... neural networks, and evolutionary algorithms. Parts five and six present supporting and advanced methods in Data Mining, such as statistical methods...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 2 pptx
... Contents XI 24 Using Fuzzy Logic in Data Mining Lior Rokach 505 Part V Supporting Methods 25 Statistical Methods for Data Mining Yoav Benjamini, Moshe Leshno 523 26 Logics for Data Mining Petr ... Determining What Is Interesting Sigal Sahar 603 31 Quality Assessment Approaches in Data Mining Maria Halkidi, Michalis Vazirgiannis 613 32 Data Mining Model Comparison P...
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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 matt...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 4 ppsx
... in data mining, Data Mining and Knowledge Discovery, 15(1):87-97, 20 07. Larose, D.T., Discovering knowledge in data: an introduction to data mining, John Wiley and Sons, 20 05. Maimon O., and ... Pub, 20 05. Wu, X. and Kumar, V. and Ross Quinlan, J. and Ghosh, J. and Yang, Q. and Motoda, H. and McLachlan, G.J. and Ng, A. and Liu, B. and Yu, P.S. an...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx
... analyze, and investigate such very large data sets has given rise to the fields of Data Mining (DM) and data warehousing (DW). Without clean and correct data the usefulness of Data Mining and data ... examining databases, detecting missing and incorrect data, and correcting errors. Other recent work relating to data cleansing includes (Bochicchio and Longo, 20...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 6 ppt
... Data Warehousing and Knowledge Discovery; 20 02 September 04-06; 170-180. Hernandez, M. & Stolfo, S. Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem, Data Mining and Knowledge ... Methods, Data Mining and Knowledge Discov- ery Handbook, Springer, pp. 321 -3 52. Simoudis, E., Livezey, B., & Kerber, R., Using Recon for Data Cleani...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 7 ppsx
... Foundations and New Directions in Data Mining, as- sociated with the third IEEE International Conference on Data Mining, Melbourne, FL, November 1 922 , 24 –30, 20 03A. Dardzinska A. and Ras Z.W. On rule discovery ... (Dardzinska and Ras, 20 03A,Dardzinska and Ras, 20 03B). Learning missing attribute values from summary constraints was reported in (Wu and Barbara, 20 02...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 8 potx
... Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_4, © Springer Science+Business Media, LLC 20 10 50 Jerzy W. Grzymala-Busse and Witold J. Grzymala-Busse Grzymala-Busse ... Newsletter 4 (20 02) 21 – 30. Wu X. and Barbara D. Modeling and imputation of large incomplete multidimensional datasets. Proc. of the 4-th Int. Con...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 9 pdf
... size, we can approximate this by the differential entropy, H(y)=− p(y)log 2 p(y)dy = 1 2 log 2 (e (2 π ) d )+ 1 2 log 2 det(C y ) (4.6) This is maximized by maximizing det(C y )=det(WCW ) over ... Q rr ≡ A+A −1 /2 BB A −1 /2 ≡U Q Λ Q U Q , then the desired matrix of orthogonal column eigen- vectors is V mr ≡ A B A −1 /2 U Q Λ −1 /2 Q (4 .24 ) (so that K mm = V Λ...
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