Suivre
Stefan Lessmann
Stefan Lessmann
Professor of Information Systems, Humboldt-University of Berlin
Adresse e-mail validée de hu-berlin.de - Page d'accueil
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Année
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
13102008
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
8342015
Annals of Information Systems
U Apte, U Karmarkar, U Kulkarni, DJ Power, R Sharda, S Kozielski, ...
3972009
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
2502006
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
1912018
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
1692017
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
1622006
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
1442016
Extreme learning machines for credit scoring: An empirical evaluation
A Bequé, S Lessmann
Expert Systems with Applications 86, 42-53, 2017
1112017
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
1072009
Predicting online shopping behaviour from clickstream data using deep learning
D Koehn, S Lessmann, M Schaal
Expert Systems with Applications 150, 113342, 2020
742020
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
692019
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
642019
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
592020
Improving crime count forecasts using Twitter and taxi data
L Vomfell, WK Härdle, S Lessmann
Decision Support Systems 113, 73-85, 2018
592018
Crowdsourcing: Systematisierung praktischer Ausprägungen und verwandter Konzepte.
N Martin, S Lessmann, S Voß
Multikonferenz Wirtschaftsinformatik, 1251-1263, 2008
562008
Targeting customers for profit: An ensemble learning framework to support marketing decision-making
S Lessmann, J Haupt, K Coussement, KW De Bock
Information Sciences 557, 286-301, 2021
542021
Solving imbalanced classification problems with support vector machines
S Lessmann
International Conference on Artificial Intelligence (ICAI), 214-220, 2004
522004
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
512011
Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning
J Engelmann, S Lessmann
Expert Systems with Applications 174, 114582, 2021
462021
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