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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Deriving Consensus Rankings from Benchmarking Experiments

Hornik, Kurt, Meyer, David January 2006 (has links) (PDF)
Whereas benchmarking experiments are very frequently used to investigate the performance of statistical or machine learning algorithms for supervised and unsupervised learning tasks, overall analyses of such experiments are typically only carried out on a heuristic basis, if at all. We suggest to determine winners, and more generally, to derive a consensus ranking of the algorithms, as the linear order on the algorithms which minimizes average symmetric distance (Kemeny-Snell distance) to the performance relations on the individual benchmark data sets. This leads to binary programming problems which can typically be solved reasonably efficiently. We apply the approach to a medium-scale benchmarking experiment to assess the performance of Support Vector Machines in regression and classification problems, and compare the obtained consensus ranking with rankings obtained by simple scoring and Bradley-Terry modeling. / Series: Research Report Series / Department of Statistics and Mathematics
2

Size-Maximal Symmetric Difference-Free Families of Subsets of [n]

Buck, Travis G., Godbole, Anant P. 01 January 2014 (has links)
Union-free families of subsets of [n] = {1, . . ., n} have been studied in Frankl and Füredi (Eur J Combin 5:127-131, 1984). In this paper, we provide a complete characterization of maximal symmetric difference-free families of subsets of [n].
3

A Complete Characterization of Maximal Symmetric Difference-Free families on {1,…<em>n</em>}.

Buck, Travis Gerarde 15 August 2006 (has links) (PDF)
Prior work in the field of set theory has looked at the properties of union-free families. This thesis investigates families based on a different set operation, the symmetricc difference. It provides a complete characterization of maximal symmetric differencefree families of subsets of {1, . . . n}

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