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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... Table 3.1 and B = A, K A (1)={1 ,4, 5}∩{1,3,6} = {1}, K A (2) = {2} ∩ {2, 4, 6,8}∩ {2, 4, 5, 7} = {2} , K A (3)={3,7}∩{1,3,6} = {3}, K A (4) ={1 ,4, 5}∩ {2, 4, 6, 8}∩ {2, 4, 5,7} = {4} , K A (5)={1 ,4, 5}∩ {2, 4, 5, 7} = {4, 5}, K A (6)={6,7}∩ {2, 4, 6,8}∩{1, ... 8}∩ {2, 4, 5,7,8}= {2, 8}, K A (3)={1,3,5,7}∩{1,3, 6, 8} = {1,3}, K A (4) ={1,3 ,4, 5,8}∩{1, 2, 4, 5,6, 8}∩ {2, 4, 5...
Ngày tải lên: 04/07/2014, 05:21
... 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 ... Computational Statistics and Data Analysis, 52( 9) :45 44 45 66, 20 08. Pazzani, M. Searching for dependencies in Bayesian classifiers. In Proceedings of the Fift...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 16 ppsx
... 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 ... Conference on Knowledge Discovery and Data Mining, SF, CA, 20 01. Shekhar S., Lu C. T., Zhang P., ”Detecting Graph-Based Spatial Outlier,” Intelligent Data Analysis:...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 17 ppsx
... 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. Very Large Databases, T. M. Vijayaraman and Alejandro P. ... 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.,...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 30 ppsx
... 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 ... dimensions. 14. 3.3 Extended Jaccard Measure The extended Jaccard measure was presented by (Strehl and Ghosh, 20 00) and it is defined as: s(x...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 42 ppsx
... Nature VIII (PPSN- 20 04) , LNCS 3 24 2, 1133-11 42 . Springer, 20 04. Jourdan L, Dhaenens-Flipo C and Talbi EG (20 03) Discovery of genetic and environmental interactions in disease data using evolutionary ... 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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Data Mining and Knowledge Discovery Handbook, 2 Edition part 45 ppsx
... algorithm, originated from Widrow and Hoff’s 21 Neural Networks For Data Mining 42 9 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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Data Mining and Knowledge Discovery Handbook, 2 Edition part 53 ppsx
... 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 ... Statistics and Data Analysis, 52( 9) :45 44 45 66. Ng R and Han J (19 94) Efficient and effective clustering method for spatial data mining. In: Proc. 19 94 I...
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Data Mining and Knowledge Discovery Handbook, 2 Edition part 118 ppsx
... 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 d...
Ngày tải lên: 04/07/2014, 06:20