Titlebook: Classification - the Ubiquitous Challenge; Proceedings of the 2 Claus Weihs,Wolfgang Gaul Conference proceedings 2005 Springer-Verlag Berli

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indices

Multimedia Pattern Recognition in Soccer Video Using Time Intervalssoccer video, we compare three different machine learning techniques, i.c. C4.5 decision tree, Maximum Entropy, and Support Vector Machine. It was found that by using the TIME framework the amount of video a user has to watch in order to see almost all highlights can be reduced considerably, especially in combination with a Support Vector Machine.

壯觀的游行

Quantitative Assessment of the Responsibility for the Disease Load in a Populatione concept of partial . has been developed. The partial . offers a unique solution for allocating shares of . to a number of exposure factors of interest, as illustrated by data from the German G?ttingen Risk, Incidence, and Prevalence Study (G.R.I.P.S.).

強(qiáng)行引入

Bagging, Boosting and Ordinal Classificationnts of bagging and boosting, which make use of the ordinal structure and it is shown how the predictive power might be improved. Comparisons are based not only on misclassification rates but also on general distance measures, which reflect the difference between true and predicted class.

Feckless

GROG

Iterative Majorization Approach to the Distance-based Discriminant Analysislems, and can be applied as a dimensionality reduction technique. In the latter case, the number of necessary discriminative dimensions can be determined exactly. The sought transformation is found as a solution to an optimization problem using iterative majorization.

GROG

left-ventricle

What Drives Serendipity Research?,ng the jack-knife procedure, and by Kiers (2004) for CP and Tucker3 analysis using the bootstrap procedure. The present paper reviews the latter procedures, discusses their performance as reported by Kiers (2004), and illustrates them on an example data set.

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地名表

Lisa N. Fink,J. César Félix-Brasdefere concept of partial . has been developed. The partial . offers a unique solution for allocating shares of . to a number of exposure factors of interest, as illustrated by data from the German G?ttingen Risk, Incidence, and Prevalence Study (G.R.I.P.S.).