Friedrich Leisch
University of Natural Resources and Life Sciences, Vienna
230 Papers
917 Citations
Friedrich Leisch is an academic researcher from University of Natural Resources and Life Sciences, Vienna. The author has contributed to research in topics: Market segmentation & Computer science. The author has an hindex of 49, co-authored 219 publications. Previous affiliations of Friedrich Leisch include Vienna University of Technology & University of Erlangen-Nuremberg.
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Papers
The sustainability–profitability trade-off in tourism: can it be overcome?
TL;DR: This paper explored a perceived trade-off between minimising environmental damage and maximising revenue, by finding market segments that are environmentally friendly and have high expenditures, and found that tourist segments vary significantly in terms of their environmental impacts and vacation expenditure.
Competitive Learning for Binary Valued Data
Friedrich Leisch,Andreas Weingessel,Evgenia Dimitriadou +2 more
- 02 Sep 1998
TL;DR: A new approach for using online competitive learning on binary data, where the usual Euclidean distance is replaced by binary distance measures, which take possible asymmetries of binary data into account and therefore provide a “different point of view” for looking at the data.
Temporal patterns of roe deer traffic accidents: Effects of season, daytime and lunar phase.
TL;DR: In this article, the authors examined the influence of different time units (i.e., season, month, day of week, and day of year) and illumination categories on deer-vehicle accidents by performing linear and generalized additive models.
A polymorphism (5-HTTLPR) in the serotonin transporter promoter gene is associated with DSM-IV depression subtypes in seasonal affective disorder.
Matthäus Willeit,Nicole Praschak-Rieder,Alexander Neumeister,Peter Zill,Friedrich Leisch,J. Stastny,E. Hilger,N. Thierry,Anastasios Konstantinidis,Dietmar Winkler,Karoline Fuchs,Werner Sieghart,Harald N. Aschauer,Manfred Ackenheil,Brigitta Bondy,Siegfried Kasper +15 more
TL;DR: Genotype distribution and allele frequencies were strongly associated with DSM-IV depression subtypes and are compatible with the hypothesis of a disease process that is not causally related to 5-HTTLPR, but involves5-HT neurotransmission and 5- HTTLPR somewhere on its way to phenotypic disease expression.
Weighted and robust archetypal analysis
TL;DR: The original algorithm is adapted to be a robust M-estimator and an iteratively reweighted least squares fitting algorithm is presented, and the weighted archetypal problem is formulated and solved.