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          Detra Note 2022-1 | Insurance analytics with k-means and extensions
          13/01/2022
          Lunch & Learn: “Features with flat partial dependence plots up to a certain level – not important?”
          03/02/2022
          Lunch & Learn “Insurance Analytics: clustering techniques”
          We are pleased to announce that our next Lunch & Learn will take place on Fev. 17, 2022 from 12:30 to 13:30.

          Get your free access now!

          It will be given in French with material in English by our Scientific Director, Donatien Hainaut, Ph.D.
          You follow this session online or onsite.
          This Lunch and Learn proposes to discuss the results of our Detranote"Insurance analytics with k-means and extensions".

          The k-means algorithm and its variants are popular techniques of clustering. Their purpose is to uncover group structures in a dataset. In actuarial applications, these methods detect clusters of policies with similar features and allows to draw a map of dominant risks. This L&L starts with a review of the k-means algorithm and develops next two extensions to manage categorical features. We present a mini-batch version that keeps computation time under control when analysing a high-dimensional dataset. We next introduce the fuzzy k-means in which policies can belong to multiple clusters. Finally, we conclude by a detailed introduction to spectral clustering.
          I'd like to participate!
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