We have the pleasure, thanks to the support of the ESSEC IDS dpt, Institut des Actuaires, LabEx MME-DII, and and the group BFA (SFdS), to invite:
Prof. Yannis YATRACOS
Cyprus University of Technology
who will speak on
Detecting clusters in the data from variance decompositions of its projections
Date and place: Thursday, May 2, at 12:30 pm, EEE - ESSEC La Défense room 202 / at 6:30 pm, ESSEC Asia Pacific - Level 3, classroom 7
Abstract: A new Projection-Pursuit Index, J, is used to identify clusters and other structures in multivariate data. Index J is obtained from an unusual variance decomposition of the data's one-dimensional projections, without assuming a model for the data or that the number of clusters is known. The Index is affine invariant and successful with real and simulated data. A general result is obtained indicating that clusters' separation increases with the data's dimension. In simulations it is thus confirmed, as expected, that the performance of the index either improves or does not deteriorate when the data's dimension increases, making it especially useful for ``large dimension-small sample size'' data, unlike other cluster detection methods. The efficiency of Index J will increase with the continuously improved computer technology and by providing additional projection directions, suitable for specific distributional assumptions. Applications and open problems are presented.
Jeremy Heng, Olga Klopp, Marie Kratz, Isabelle Wattiau