O sodobnih metodah gručenja, Fuzzy C-means gručenju in osnovah algoritma MOO (Multi-Objective Optimization) bo predavala profesorica Sanghamitra Bandyopadhyay, direktorica Indijskega statističnega inštituta v Kolkati. Vidimo se v ponedeljek, 14. novembra 2016, ob 10.15 v predavalnici 4 na Fakulteti za računalništvo in informatiko UL.

Multiobjective clustering

Abstract:

The problem of clustering is essentially one of optimization. In past, metaheuristic methods like genetic algorithms have been used for clustering a data set. Yet, the clustering problem admits a number of criteria or cluster validity indices that have to be simultaneously optimized. Hence in recent times the problem has posed in a Multi-Objective Optimization (MOO) framework and popular metaheuristics for multiobjective optimization have been applied. In this talk, we will first briefly discuss about the Fuzzy C-means Algorithm, followed by an introduction to the basic principles of MOO and a popular MOO algorithm. Subsequently it will be shown how the algorithm is useful for solving the clustering problem. Since such algorithms provide a number of solutions, a way of combining the multiple clustering solutions so obtained into a single one using supervised learning will be explained. Finally, results will be demonstrated on clustering of some popular gene expression data sets.

Predavanje bo potekalo v angleščini.