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Learning cost sensitive binary classification rules accounting for uncertain and unequal misclassification costs
Rybizki, Lydia - 2014
supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …
Persistent link: https://www.econbiz.de/10010334218
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Learning cost sensitive binary classification rules accounting for uncertain and unequal misclassification costs
Rybizki, Lydia - 2014
supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …
Persistent link: https://www.econbiz.de/10010250581
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Performance of credit risk prediction models via proper loss functions
Figiani, Silvia Figini; Maggi, Mario - Dipartimento di Scienze Economiche e Aziendali, … - 2014
recently been proposed that can be seen as refinements of discrimination measures, including variants of the AUC (Area Under … the ROC curve), such as the H index. It is widely recognized that AUC suffers from lack of coherency especially when ROC …
Persistent link: https://www.econbiz.de/10010842822
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Data analytics for non-life insurance pricing
Wüthrich, Mario V.; Buser, Christoph - 2017 - Draft lecture notes, version January 27, 2017
regression trees, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …
Persistent link: https://www.econbiz.de/10011625588
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Improved customer choice predictions using ensemble methods
van Wezel, van Wezel, M.C.; Potharst, Potharst, R. - Faculteit der Economische Wetenschappen, Erasmus … - 2005
In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved...
Persistent link: https://www.econbiz.de/10010731879
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Improved customer choice predictions using ensemble methods
Wezel, M.C. van; Potharst, R. - Erasmus University Rotterdam, Econometric Institute - 2005
In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved...
Persistent link: https://www.econbiz.de/10005450872
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AUK: a simple alternative to the AUC
Kaymak, Uzay; Ben-David, Ben-David, A.; Potharst, … - Erasmus Research Institute of Management (ERIM), … - 2010
The area under Receiver Operating Characteristic (ROC) curve, also known as the AUC-index, is commonly used for ranking … the performance of data mining models. The AUC has many merits, such as objectivity and ease of interpretation. However … proposed AUK-index compensates for the above basic flaw of the AUC by being sensitive to the class distribution. Therefore it …
Persistent link: https://www.econbiz.de/10010731206
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AUK: a simple alternative to the AUC
Kaymak, Uzay; Ben-David, A.; Potharst, R. - Erasmus Research Institute of Management (ERIM), ERIM … - 2010
The area under Receiver Operating Characteristic (ROC) curve, also known as the AUC-index, is commonly used for ranking … the performance of data mining models. The AUC has many merits, such as objectivity and ease of interpretation. However … proposed AUK-index compensates for the above basic flaw of the AUC by being sensitive to the class distribution. Therefore it …
Persistent link: https://www.econbiz.de/10008484125
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Big Data Analytics: A New Perspective
Chudik, Alexander; Kapetanios, George; Pesaran, M. Hashem - 2016
Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...
Persistent link: https://www.econbiz.de/10011451442
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Big data analytics : a new perspective
Chudik, Alexander; Kapetanios, George; Pesaran, M. Hashem - 2016
Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...
Persistent link: https://www.econbiz.de/10011444508