Data Mining and Knowledge Discovery Handbook, 2 Edition part 12 ppsx

... Springer, pp. 178-196, 20 02. Maimon, O. and Rokach, L., Decomposition Methodology for Knowledge Discovery and Data Mining: Theory and Applications, Series in Machine Perception and Artificial In- telligence ... lr18,lr14, Security lr7,l10 and Medicine lr2,lr9, and for many data mining techniques, such as: decision trees lr6,lr 12, lr15, clustering lr13,lr8, ensemble...

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... 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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... 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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... Conference on Data- mining (ICDM’ 02) , Maebashi City, Japan, CSIRO Technical Report CMIS- 02/ 1 02, 20 02. Williams G. J., Huang Z., Mining the knowledge mine: The hot spots methodology for mining large ... phenomena). When data is limited, it is common practice to re-sample the data, that is, partition the data into training and test sets in different ways. An inducer is tr...

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... 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, O., Data mining for improving the quality of manufacturing: ... 14: 2, 24 1-301, 20 02. Shafer, J. C., Agrawal, R. and Mehta, M. , SPRINT: A Scalable Parallel Classifier for Data Mining, Proc. 22 nd Int. Conf...

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... as: d(x i ,x j )=(w 1   x i1 −x j1   g + w 2   x i2 −x j2   g + +w p   x ip −x jp   g ) 1/g where w i ∈ [0,∞) 27 8 Lior Rokach can be interpreted as agreements, and b and c as disagreements. The Rand index is defined as: RAND ... + b + c + d The Rand index lies between 0 and 1. When the two partitions agree perfectly, the Rand index is 1. A problem with the Rand index is t...

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... Kluwer. Freitas AA (20 01) Understanding the crucial role of attribute interaction in data mining. Artificial Intelligence Review 16(3), 177-199. Freitas AA (20 02a) Data Mining and Knowledge Discovery with ... data mining: a position paper. ACM SIGKDD Explorations, 6 (2) , 77-86, Dec. 20 04. Freitas AA (20 05) Evolutionary Algorithms for Data Mining. In: O. Maimon and L...

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... algorithm, originated from Widrow and Hoff’s 21 Neural Networks For Data Mining 429 in-sample and out-of-sample if the data size is very large. Typical split in data mining applications reported in ... useful data mining model. There are several practical issues around the data requirement for a neural net- work model. The first is the data quality. As data sets used...

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... with data mining. Since fuzzy O. Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4 _24 , © Springer Science+Business Media, LLC 20 10 23 ... Conference on Data Mining, IEEE Computer Society Press, pp. 473–480, 20 01. Rokach L and Maimon O (20 05), Clustering Methods, Data Mining and Knowledge Discov...

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... Maimon, L. Rokach (eds.), Data Mining and Knowledge Discovery Handbook, 2nd ed., DOI 10.1007/978-0-387-09 823 -4_60, © Springer Science+Business Media, LLC 20 10 60 Data Mining for Financial Applications ... formula 63.1 have an interpretation. 60 .2. 2 Data selection and forecast horizon Data Mining in finance has the same challenge as general Data Mining in da...

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