Stefan Lessmann
Stefan Lessmann
Professor of Information Systems, Humboldt-University of Berlin
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Zitiert von
Zitiert von
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
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
Annals of Information Systems
U Apte, U Karmarkar, U Kulkarni, DJ Power, R Sharda, S Kozielski, ...
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
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
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
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
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
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
Extreme learning machines for credit scoring: An empirical evaluation
A Bequé, S Lessmann
Expert Systems with Applications 86, 42-53, 2017
Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte.
N Martin, S Lessmann, S Voß
Multikonferenz Wirtschaftsinformatik, 1251-1263, 2008
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
Solving imbalanced classification problems with support vector machines
S Lessmann
International Conference on Artificial Intelligence (ICAI), 214-220, 2004
Spurious patterns in Google Trends data-An analysis of the effects on tourism demand forecasting in Germany
B Bokelmann, S Lessmann
Tourism management 75, 1-12, 2019
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
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
Targeting customers for profit: An ensemble learning framework to support marketing decision-making
S Lessmann, J Haupt, K Coussement, KW De Bock
Information Sciences, 2019
Optimizing hyperparameters of support vector machines by genetic algorithms.
S Lessmann, R Stahlbock, SF Crone
IC-AI, 74-82, 2005
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
Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting
A Kim, Y Yang, S Lessmann, T Ma, MC Sung, JEV Johnson
European Journal of Operational Research 283 (1), 217-234, 2020
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