Stefan Lessmann
Stefan Lessmann
Professor of Information Systems, Humboldt-University of Berlin
Bestätigte E-Mail-Adresse bei hu-berlin.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Benchmarking classification models for software defect prediction: A proposed framework and novel findings
S Lessmann, B Baesens, C Mues, S Pietsch
IEEE Transactions on Software Engineering 34 (4), 485-496, 2008
10532008
Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research
S Lessmann, B Baesens, HV Seow, LC Thomas
European Journal of Operational Research 247 (1), 124-136, 2015
5012015
Annals of Information Systems
U Apte, U Karmarkar, U Kulkarni, DJ Power, R Sharda, S Kozielski, ...
3602009
The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing
SF Crone, S Lessmann, R Stahlbock
European Journal of Operational Research 173 (3), 781-800, 2006
2062006
Genetic algorithms for support vector machine model selection
S Lessmann, R Stahlbock, SF Crone
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
1412006
A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry
K Coussement, S Lessmann, G Verstraeten
Decision Support Systems 95, 27-36, 2017
992017
Bridging the divide in financial market forecasting: machine learners vs. financial economists
MW Hsu, S Lessmann, MC Sung, T Ma, JEV Johnson
Expert Systems with Applications 61, 215-234, 2016
952016
A reference model for customer-centric data mining with support vector machines
S Lessmann, S Voß
European Journal of Operational Research 199 (2), 520-530, 2009
892009
A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data
S Srivastava, S Lessmann
Solar Energy 162, 232-247, 2018
852018
Extreme learning machines for credit scoring: An empirical evaluation
A Bequé, S Lessmann
Expert Systems with Applications 86, 42-53, 2017
612017
Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte.
N Martin, S Lessmann, S Voß
Multikonferenz Wirtschaftsinformatik, 1251-1263, 2008
512008
Tuning metaheuristics: A data mining based approach for particle swarm optimization
S Lessmann, M Caserta, IM Arango
Expert Systems with Applications 38 (10), 12826-12838, 2011
452011
Solving imbalanced classification problems with support vector machines
S Lessmann
International Conference on Artificial Intelligence (ICAI), 214-220, 2004
422004
Utility based data mining for time series analysis: cost-sensitive learning for neural network predictors
SF Crone, S Lessmann, R Stahlbock
Proceedings of the 1st international workshop on Utility-based data mining …, 2005
392005
Identifying winners of competitive events: A SVM-based classification model for horserace prediction
S Lessmann, MC Sung, JEV Johnson
European Journal of Operational Research 196 (2), 569-577, 2009
332009
Forecasting with computational intelligence-an evaluation of support vector regression and artificial neural networks for time series prediction
SF Crone, S Lessmann, S Pietsch
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
322006
Alternative methods of predicting competitive events: An application in horserace betting markets
S Lessmann, MC Sung, JEV Johnson
International Journal of Forecasting 26 (3), 518-536, 2010
292010
A multi-objective approach for profit-driven feature selection in credit scoring
N Kozodoi, S Lessmann, K Papakonstantinou, Y Gatsoulis, B Baesens
Decision Support Systems 120, 106-117, 2019
262019
Optimizing hyperparameters of support vector machines by genetic algorithms.
S Lessmann, R Stahlbock, SF Crone
IC-AI, 74-82, 2005
262005
A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction
MC Sung, S Lessmann, JEV Johnson, T Ma
European Journal of Operational Research 218 (1), 163-174, 2012
242012
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