Claus Weihs
Claus Weihs
Professor für Computergestützte Statistik, TU Dortmund
Verified email at - Homepage
Cited by
Cited by
klaR analyzing German business cycles
C Weihs, U Ligges, K Luebke, N Raabe
Data analysis and decision support, 335-343, 2005
Exploratory landscape analysis
O Mersmann, B Bischl, H Trautmann, M Preuss, C Weihs, G Rudolph
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
Resampling methods for meta-model validation with recommendations for evolutionary computation
B Bischl, O Mersmann, H Trautmann, C Weihs
Evolutionary computation 20 (2), 249-275, 2012
Data science: the impact of statistics
C Weihs, K Ickstadt
International Journal of Data Science and Analytics 6, 189-194, 2018
Classification of high and low achievers in a music sight-reading task
R Kopiez, C Weihs, U Ligges, JI Lee
Psychology of Music 34 (1), 5-26, 2006
On the distribution of the desirability index using Harrington’s desirability function
H Trautmann, C Weihs
Metrika 63, 207-213, 2006
Variable window adaptive kernel principal component analysis for nonlinear nonstationary process monitoring
IB Khediri, M Limam, C Weihs
Computers & Industrial Engineering 61 (3), 437-446, 2011
Model-based multi-objective optimization: taxonomy, multi-point proposal, toolbox and benchmark
D Horn, T Wagner, D Biermann, C Weihs, B Bischl
International Conference on Evolutionary Multi-Criterion Optimization, 64-78, 2015
Classification in music research
C Weihs, U Ligges, F Mörchen, D Müllensiefen
Advances in Data Analysis and Classification 1, 255-291, 2007
Desirability-Based Multi-Criteria Optimization of HVOF Spray Experiments to Manufacture Fine Structured Wear-Resistant 75Cr3C2-25(NiCr20) Coatings
W Tillmann, E Vogli, I Baumann, G Kopp, C Weihs
Journal of thermal spray technology 19, 392-408, 2010
MOI-MBO: multiobjective infill for parallel model-based optimization
B Bischl, S Wessing, N Bauer, K Friedrichs, C Weihs
Learning and Intelligent Optimization: 8th International Conference, Lion 8 …, 2014
Tuning and evolution of support vector kernels
P Koch, B Bischl, O Flasch, T Bartz-Beielstein, C Weihs, W Konen
Evolutionary Intelligence 5, 153-170, 2012
Kernel k-means clustering based local support vector domain description fault detection of multimodal processes
IB Khediri, C Weihs, M Limam
Expert Systems with Applications 39 (2), 2166-2171, 2012
Statistische Methoden zur Qualitätssicherung und-optimierung in der Industrie
C Weihs, J Jessenberger, YL Grize
Wiley-Vch, 1999
BatchJobs and BatchExperiments: Abstraction mechanisms for using R in batch environments
B Bischl, M Lang, O Mersmann, J Rahnenführer, C Weihs
Journal of Statistical Software 64, 1-25, 2015
Monitoring a deep hole drilling process by nonlinear time series modeling
A Messaoud, C Weihs
Journal of Sound and Vibration 321 (3-5), 620-630, 2009
Analyzing the BBOB results by means of benchmarking concepts
O Mersmann, M Preuss, H Trautmann, B Bischl, C Weihs
Evolutionary computation 23 (1), 161-185, 2015
Music data analysis: Foundations and applications
C Weihs, D Jannach, I Vatolkin, G Rudolph
Chapman and Hall/CRC, 2016
Automatic model selection for high-dimensional survival analysis
M Lang, H Kotthaus, P Marwedel, C Weihs, J Rahnenführer, B Bischl
Journal of Statistical Computation and Simulation 85 (1), 62-76, 2015
Data analysis and decision support
C Weihs, U Ligges, K Luebke, N Raabe, D Baier, R Decker, ...
Springer Verlag, Berlin, 2005
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