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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

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

Examining the information content of residuals from hedonic and spatial models using trees and forests

Pace, R. Kelley; Hayunga, Darren - In: The journal of real estate finance and economics 60 (2020) 1/2, pp. 170-180

Persistent link: https://www.econbiz.de/10012226654

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