Banca de DEFESA: DANIEL NOBRE PINHEIRO

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : DANIEL NOBRE PINHEIRO
DATE: 16/12/2020
TIME: 14:00
LOCAL: videoconferencia
TITLE:

Convex fuzzy k-medoids clustering

KEY WORDS:

Fuzzy clustering, Convex optimization, Multiple representatives.

PAGES: 81
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

The k-medoids model is one of the most popular clustering methods. In this work, we propose the Convex Fuzzy k-Medoids Problem (CFKM), which not only allows one object to be assigned to multiple clusters, but also allows a cluster to be represented by multiple medoids. The proposed model is convex and thus is robust to initialization. To evaluate the importance of CFKM, we compare it with another two fuzzy k-medoids models: the Fuzzy k-Medoids Problem (FKM) and the Fuzzy clustering with Multi-Medoids Problem (FMMdd), both solved by heuristics due to their computational complexity. Experiments with both synthetic and real-world data, along with an user survey, show that CFKM is not only more robust to the choice of parameters of fuzzy models, but also is the only able to reveal important aspects of inherently fuzzy data.

BANKING MEMBERS:
Presidente - 1746084 - DANIEL ALOISE
Interno - 1673543 - SAMUEL XAVIER DE SOUZA
Externa ao Programa - 1746062 - CAROLINE THENNECY DE MEDEIROS ROCHA
Externo à Instituição - ERALDO LUIS REZENDE FERNANDES - UFMS
Externa à Instituição - MARIÁ CRISTINA VASCONCELOS NASCIMENTO ROSSET - UNIFESP