10 e 11 gennaio 2019
LIUC Università Cattaneo
Relatore: Dott.ssa Cristina Tortora
Assistant Professor, Department of Mathematics and Statistics - San Jose State University
All’interno del ciclo di seminari rivolti ai docenti e ricercatori LIUC, programmati dal Prorettore per rendere meglio noti i temi presidiati in Università e dare modo a tutti i ricercatori di presentare i loro lavori con l’intento di costruire nuove collaborazioni di ricerca, la Dott.ssa Cristina Tortora - Assistant Professor, Department of Mathematics and Statistics - San Jose State University, ha tenuto un seminario dal titolo “Model based clustering”.
Il seminario è stato promosso internamente dalla Dott.ssa Marta Nai Ruscone (Scuola Economia e Management della LIUC – Università Cattaneo).
Abstract
Cluster analysis is a multivariate statistical technique that identifies homogeneous groups of units within the data. One of the most commonly used technique is model based clustering. Model based clustering assumes that a population is a mixture of sub-population, each component is modeled through a probability density function and a component can be considered a cluster. The scope of this short course is to introduce model based clustering on continuous data. The course will start with the introduction of the most traditional model, Gaussian mixture models, with some details on the algorithm. Some flexible techniques, based on non-Gaussian distributions, will then be introduced. The last topic covered will be the recently proposed mixture of contaminated normal distributions, that has the advantage of simultaneously clustering the data and detecting outliers.
The course will also contains a brief tutorial on some R packages for the presented models.
Ufficio Ricerca
ricerca@liuc.it
