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... 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 ... we diagonalize 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 Q V  and ... − d  ∑ a=1 ( d ∑ p=1 β ap e  p )C( d ∑ q=1 β aq e q )=− d  ∑ a=1 d ∑ p=1 λ p β 2 ap Introducing Lagrange multipliers ω ab to enforce the orthogonality constraints (Burges, 20 04), the objective function becomes F = d  ∑ a=1 d ∑ p=1 λ p β 2 ap − d  ∑ a,b=1 ω ab  d ∑ p=1 β ap β bp − δ ab  (4.5) Choosing 8 ω ab ≡ ω a δ ab and...

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... and L.K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 29 0 (22 ) :23 23 23 26, 20 00. I.J. Schoenberg. Remarks to maurice frechet’s article sur la d ´ efinition axiomatique ... Neural Information Processing Systems 15, pages 705–7 12. MIT Press, 20 02. P. Diaconis and D. Freedman. Asymptotics of graphical projection pursuit. Annals of Statis- tics, 12: 793–815, 1984. K.I. Diamantaras and ... Analysis and Machine Intelligence, 26 (2) , 20 04. J.H. Friedman and W. Stuetzle. Projection pursuit regression. Journal of the American Statistical Association, 76(376):817– 823 , 1981. J.H. Friedman, W....

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... Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_14, © Springer Science+Business Media, LLC 20 10 26 2 Jerzy W. Grzymala-Busse The partial star G(5|3) covers cases 6 ... lists. Machine Learning 1987; 2: 22 9 24 6. Stefanowski J. Algorithms of Decision Rule Induction in Data Mining. Poznan University of Technology Press, Poznan, Poland, 20 01. Weiss S. and Kulikowski ... (ed.), The MIT Press, Boston, MA, 1990, 23 5 28 2. Chan C.C. and Grzymala-Busse J.W. On the attribute redundancy and the learning programs ID3, PRISM, and LEM2. Department of Computer Science, University...

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... Data Mining, 32- 41, 20 02 Tsoukatos, I. and Gunopulos, D. Efficient Mining of Spatiotemporal Patterns. Proc. Int. Symp. Spatial and Temporal Databases, LNCS 21 21, pages 425 -4 42, 20 01 Wang J., Han ... SIGMOD Record 26 (2) :25 5 -26 4, 1997 Castelo R., Feelders A., Siebes A. Mambo: Discovering Association Rules. Proc. Symp. on Intelligent Data Analysis. LNCS 21 89, 28 9 -29 8, Springer, 20 01 Clark P., ... Intelligent Data Analysis, 6(3) :23 7 -25 6, 20 02 H ¨ oppner F. Discovery of Core Episodes from Sequences. Proc. Pattern Detection and Dis- covery, LNAI 24 47, 199 -21 3, Springer, 20 02 Klemettinen M., Mannila...

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... about the product (Domingos, 1996, Richardson, 20 02, Kempe et al., 20 03). A famous example of viral market- ing is the rapid spread of Hotmail as a free email service. Attached to each email was ... often far from the truth. Work in the area of link completion (Kubica et al., 20 02, Goldenberg et al., 20 03,Kubica et al., 20 03) induces missing links from previously observed data. This allows users ... the Seventh International Conference on Knowledge Discovery and Data Mining; 20 01 Au- gust 26 – 29 ; San Francisco, CA. ACM Press, 20 01. Donoho S. & Lewis S. Understand behavior detection technology:...

Ngày tải lên: 04/07/2014, 05:21

... Medical Informat- ics (MEDINFO 20 04), San Francisco, CA, September 20 04, IOS Press, pp. 28 2 28 6. Bellman R. Dynamic Programming. Princeton University Press, 1957. 4 12 Oded Maimon and Shahar Cohen meet ... Springer-Verlag, 20 03, pp. 24 –31. Rokach, L. and Maimon, O. and Averbuch, M., Information Retrieval System for Medical Narrative Reports, Lecture Notes in Artificial intelligence 3055, page 21 7 -22 8 Springer- Verlag, ... Data Analysis, Volume 9, Number 2, 20 05b, pp 131–158. Rokach, L. and Maimon, O., Clustering methods, Data Mining and Knowledge Discovery Handbook, pp. 321 –3 52, 20 05, Springer. Rokach, L. and Maimon,...

Ngày tải lên: 04/07/2014, 05:21

... with neighbors (Partridge and Pitcher, 1980,Partridge, 19 82) . Couzin et al. (20 02) identified four collective dynamical behaviors as illustrated in Figure 2: 1. Swarm: an aggregate with cohesion, ... 1997, Ko- honen, 1995, Falkenauer, 1998, Paterlini and Minerva, 20 03, Xu and Wunsch, 20 05, Rokach and Maimon, 20 05, Mitra et al .20 02) . One of the most popular approaches in this direction has been ... j-th real value feature (j = 1, 2, ,d)ofthei-th pattern ( i =1 ,2, , n). Given such an Xn×d , a partitional clustering algorithm tries to find a partition C = {C1, C2, , Ck}of k classes, such that...

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... 19 -22 , 20 03, pp. 115- 122 . H. Kargupta, Park, B., Pittie, S., Liu, L., Kushraj, D. and Sarkar, K. (20 02) . MobiMine: Monitoring the Stock Market from a PDA. ACM SIGKDD Explorations. January 20 02. Volume ... area. Aurora (Abadi et al., 20 03), COUGAR (Yao and Gehrke, 20 02) , Gigascope (Cra- nor et al., 20 03), STREAM (Arasu et al., 20 03), TelegraphCQ (Krishnamurthy et al., 20 03) represent the first generation ... data is a research topic of growing interest (Bab- cock et al., 20 02, Chen et al., 20 02, Domingos and Hulten, 20 00, Hulten et al., 20 01). The fundamental problem we need to solve is the following:...

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... GIScience pp 27 1– 28 8 Berndt DJ, Clifford J (1996) Finding patterns in time series: a dynamic programming ap- proach. Advances in knowledge discovery and data mining pp 22 9 24 8 Birant D, Kut A (20 06) ... NY, USA, pp 21 6 22 5 Wang M, Wang A, Li A (20 06) Mining Spatial-temporal Clusters from Geo-databases. Lec- ture Notes in Computer Science 4093 :26 3 Zhang P, Huang Y, Shekhar S, Kumar V (20 03) Correlation ... 35 92- 36 12, 20 07. Ester M, Kriegel HP, Sander J, Xu X (1996) A density-based algorithm for discovering clus- ters in large spatial databases with noise. Data Mining and Knowledge Discovery pp 22 6 23 1 Fosca...

Ngày tải lên: 04/07/2014, 05:21

... rule big spender(C1,Age1,Income1,TotalSpent1) ← married to(C1,C2) ∧ customer(C2,Age2,Income2,TotalSpent2,BS2) ∧ Income2 ≥ 108000. 46.1 .2 Relational Patterns Relational patterns involve multiple relations ... 21 4000 18800 Yes c2 Female 19 139000 15100 Yes c3 Male 55 50000 124 00 No c4 Female 48 26 000 8600 No c5 Male 63 191000 28 100 Yes c6 Male 63 114000 20 400 Yes c7 Male 58 38000 11800 No c8 Male 22 ... 67–77. Japkowicz, N. (20 01b). Supervised versus unsupervised binary-learning by feedforward neu- ral networks. Machine Learning, 42( 1 /2) :97– 122 . Jo, T. and Japkowicz, N. (20 04). Class imbalances...

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... sites (Perkowitz and Etzioni, 20 00, Berendt, 20 02) , personalizing web services (Mobasher et al., 20 00, Mobasher et al., 20 02, Pierrakos et al., 20 03), optimizing search engines (Joachims, 20 02) , recognizing ... from web data. SIGKDD explorations, 1 (2) : 12 23 , 20 00. S. Staab and A. Maedche. Knowledge portals — ontologies at work. AI Magazine, 21 (2) :63– 75, Summer 20 01. S. Staab, A. Maedche, C. N ´ edellec, ... Artificial Intelligence (AAAI -20 02) , pages 187–1 92, Edmonton, Canada, 20 02. D. Mladeni ´ c. Personal WebWatcher: Implementation and design. Technical Report IJS-DP- 74 72, Department of Intelligent...

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... are gaining momentum in different fields (Muggleton, 20 02, D ˇ zeroski, 20 02, Thu- lasiram, 1999, Neville and Jensen, 20 02, Vityaev et al., 20 02) . Data Mining in finance not only follows this trend ... Stochastic Logic Programs, 12th In- ternational Conference, ILP 20 02, Sydney, Australia, July 9-11, 20 02. Lecture Notes in Computer Science 25 83 Springer 20 03, 198 -20 6. Muggleton S., Scientific ... Information Systems, 17(4), 20 01, 20 3 -22 2, 20 01. Wang, H., Weigend A. (Eds), Data Mining for financial decision making, Special Issue, Decision support systems, Volume 37, Issue 4 ,20 04. Wang J., Data...

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