The following pages link to Stefan Lessmann (Q319940):
Displaying 15 items.
- Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research (Q319944) (← links)
- (Q439472) (redirect page) (← links)
- A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction (Q439474) (← links)
- Identifying winners of competitive events: a SVM-based classification model for horserace prediction (Q1027543) (← links)
- A reference model for customer-centric data mining with support vector machines (Q1042173) (← links)
- Fairness in credit scoring: assessment, implementation and profit implications (Q2060424) (← links)
- Cost-sensitive business failure prediction when misclassification costs are uncertain: a heterogeneous ensemble selection approach (Q2183867) (← links)
- Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid (Q2203392) (← links)
- Targeting customers under response-dependent costs (Q2242231) (← links)
- Response transformation and profit decomposition for revenue uplift modeling (Q2286984) (← links)
- The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing (Q2497261) (← links)
- Data-driven support for policy and decision-making in university research management: a case study from Germany (Q6167419) (← links)
- Improving uplift model evaluation on randomized controlled trial data (Q6555155) (← links)
- Explainable AI for operational research: a defining framework, methods, applications, and a research agenda (Q6572853) (← links)
- Exploiting time-varying RFM measures for customer churn prediction with deep neural networks (Q6589106) (← links)
