Description:

Successful participation in the module “Methoden der Ökonometrie” is recommended.

The syllabus includes: statistical and machine learning methods, in particular: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical).

Literature:

James, Gareth, et al. An introduction to statistical learning. Vol. 112. No. 1. New York: springer, 2013.

Formalities:

Die Veranstaltung befasst sich mit dem Thema 'Statistical Learning' und wird als Block angeboten.

Weitere Informationen folgen in Kürze.

Links:

Informationen zur Anrechenbarkeit sowie den Inhalten dieser Veranstaltung finden sich im Modulhandbuch.