13/09/2021
Cluster analysis is the task of grouping a set of objects (e.g., observations, policies, claims) in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups. In contrast to simple segmentation (e.g. by geographical location only), clustering uses several features to differentiate among those groups. Potential applications are manifold and centred around questions such as, for example:
Join our EAA web session "Advanced Concepts of Clustering in
Insurance" on 25 November 2021 | 10:00-12:00 CET!
The web session shows how different algorithms can be used to
obtain a segmentation of insurance data. The methods covered range
from centroid-based (k-means, k-prototypes) to probabilistic
(Gaussian Mixture Models) and density-based (DBSCAN) approaches. We
demonstrate how the clustering results can be visualized and
evaluated. Moreover, it will be shown how the clustering results
can be used to identify outliers in the data set. We also cover
techniques that reduce the dimension of the data so that the
segments can be computed either on aggregated information or using
only a subset of the available information. The course puts an
emphasis on the practical application and therefore showcases all
concepts on an insurance data set.
Please find all additional information on our website or in this print version. An overview on other
upcoming actuarial events can be downloaded as well.
Your early-bird
registration fee is € 100.00 plus 19% VAT for bookings by 14
October 2021. After this date, the booking fee will be €
140.00 plus 19% VAT.