By Rainer Schmidt, Tina Waligora, Olga Vorobieva (auth.), Petra Perner (eds.)
ICDM / MLDM Medaillie (limited variation) Meissner Porcellan, the “White Gold” of King August the most powerful of Saxonia ICDM 2008 was once the 8th occasion of the economic convention on information Mining held in Leipzig (www.data-mining-forum.de). For this version this system Committee bought 116 submissions from 20 international locations. After the peer-review technique, we permitted 36 top of the range papers for oral presentation, that are incorporated in those court cases. the themes variety from facets of class and prediction, clustering, internet mining, facts mining in drugs, functions of knowledge mining, time sequence and widespread development mining, and organization rule mining. 13 papers have been chosen for poster displays which are released within the ICDM Poster continuing quantity. together with ICDM there have been 3 workshops concentrating on exact sizzling application-oriented subject matters in info mining. The workshop information Mining in lifestyles technology DMLS 2008 was once held the 3rd time this yr and the workshop facts Mining in advertising DMM 2008 ran for the second one time this yr. also, we brought a global Workshop on Case-Based Reasoning for Multimedia info CBR-MD.
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Extra info for Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects: 8th Industrial Conference, ICDM 2008 Leipzig, Germany, July 16-18, 2008 Proceedings
Greedy is the worst non-random scheme. Unitary redundancy ﬁlters come high up in third place. Fig. 2 shows changes with diﬀerent numbers of features. 1. 9 1 4 8 12 16 20 30 45 60 number of features 80 100 Fig. 2. Normalized Median Rankings of all Selection Schemes diﬀerent combinations of methods. The medians for each selection scheme are depicted in ﬁg. 2. We see that with more features all selection schemes become better than random choice because of the inclusion of less probes. MRmRQ starting as best at 4 variables, adding more features improves relatively less than most other selection schemes.
BioCyber 61, 102–113 (1989) 13. : Additive logistic regression: a statistical view of boosting, Tech. report, Department of Statistics, Stanford University (1998) 14. : Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291, 1560–1563 (2001) 15. : Normalization in support vector machines. , Florczyk, S. ) DAGM 2001. LNCS, vol. 2191, pp. 277–282. Springer, Heidelberg (2001) 16. : Result analysis of the NIPS feature selection challenge, vol. 17, pp. 545–552.
As we will see below in table 2, the probe of zeros (feature index 177), enjoyed some popularity. This seems to be a problem that comes from the skewed classdistributions in our data, which makes that 0 can be to 90% associated with one class. Table 2 lists from 4 to 100 numbers of features (ﬁrst column) the selection method (second column) that provided the best performing feature set. At the end of the second column we put the redundancy and relevance measures (cf. 2). ), random normal probes (RN), random uniform probes (RU), and the zero probe.
Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects: 8th Industrial Conference, ICDM 2008 Leipzig, Germany, July 16-18, 2008 Proceedings by Rainer Schmidt, Tina Waligora, Olga Vorobieva (auth.), Petra Perner (eds.)