Home | english  | Impressum | Sitemap | KIT

Data Mining in Credit Risk

Data Mining in Credit Risk
Typ: Seminar (S)
Semester: WS 13/14
Dozent: Dr. Markus Höchstötter
LVNr.: <a target="lvn" href="https://studium.kit.edu/meineuniversitaet/Seiten/vorlesungsverzeichnis.aspx?page=event.asp&objgguid=NEW&gguid=0xa3f1e3ba0969944494d7ad1ec77b4df5">2521389</a>

Bemerkungen:

Anmerkungen

Eine vorherige Anmeldung per Email an markus.hoechstoetter@kit.edu oder Abdolreza.nazemi@kit.edu wird erbeten.

Für weitere Informationen: http://statistik.econ.kit.edu/

Literaturhinweise (en):

1] Charu C. Aggarwal, (2011). SocialNetwork Data Analytics, Springer.

2] Engelmann, B. and R. Rauhmeier, (2011). The Basel II risk parameters: Estimation, validation, and stress testing. Springer, Berlin.

3] Tan, P. N., M. Steinbach, and V. Kumar, (2006). Introduction to Data Mining. Addison Wesley.

4] Thomas, L. C. (2009).Consumer Credit Models. Oxford, UK: OxfordUniversity Press.

5] Van Gestel, T. and B. Baesens, (2009).Credit Risk Management. Oxford, UK: Oxford University Press.

6] Tsai, C.J et al. (2008). A discretization algorithm based on Class-Attribute Contingency Coefficient, Information Sciences, Vol. 178, pp. 714-731.