Convite da defesa de dissertação do programa de pós-graduação em Ciência da Computação

A Coordenação do Programa de Pós-Graduação em Ciência da Computação tem a satisfação de convidá-lo para a Defesa de Dissertação:


Product Partition Model for Categorical Features

Tulio Lima Criscuolo


A common difficulty in data analysis is how to handle categorical predictors with a large number of levels or categories. There are few proposals developed in the literature to handle this important and frequent problem. We introduce a generative model that simultaneously carries out the model fitting and the aggregation of the categorical levels into larger groups. Our approach is based on imposing a graph where the nodes are categories and creating a probability distribution over meaningful partitions of this graph. Being a Bayesian model, it allows the posterior inference, including uncertainty measurement, on the estimated parameters and the categories partition. We compare our method with the state-of-art methods showing that it has equally good predictive performance and much better interpretation ability. Given the current concern on balancing accuracy versus interpretability, our proposal reaches an excellent result.


Comissão Examinadora:


Prof. Wagner Meira Júnior - Orientador (DCC - UFMG)

Prof. Renato Martins Assunção - Coorientador (DCC - UFMG)

Prof. Fabricio Murai Ferreira (DCC - UFMG)

Profa. Rosangela Helena Loschi (DEST - UFMG)

Prof. Denis Deratani Mauá (IME - USP)


25 de Outubro de 2019



Sala 6321 do ICEX

Última modificação em Quinta, 24 Outubro 2019 20:03