Banca de DEFESA: CARINE AZEVEDO DANTAS

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DISCENTE : CARINE AZEVEDO DANTAS
DATA : 10/02/2017
HORA: 09:00
LOCAL: Anf. A do CCET
TÍTULO:

An Unsupervised-based Feature Selection for Classication tasks


PALAVRAS-CHAVES:

Feature Selection, Classication, Clustering Algorithms


PÁGINAS: 70
GRANDE ÁREA: Ciências Exatas e da Terra
ÁREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
ESPECIALIDADE: Sistemas de Informação
RESUMO:

With the increase of the size on the data sets used in classication systems, selecting
the most relevant attribute has become one of the main tasks in pre-processing phase.
In a dataset, it is expected that all attributes are relevant. However, this is not always
veried. Selecting a set of attributes of more relevance aids decreasing the size of the data
without aecting the performance, or even increase it, this way achieving better results
when used in the data classication. The existing features selection methods elect the
best attributes in the data base as a whole, without considering the particularities of
each instance. The Unsupervised-based Feature Selection, proposed method, selects the
relevant attributes for each instance individually, using clustering algorithms to group
them accordingly with their similarities. This work performs an experimental analysis
of dierent clustering techniques applied to this new feature selection approach. The
clustering algorithms k-Means, DBSCAN and Expectation-Maximization (EM) were used
as selection method. Analyzes are performed to verify which of these clustering algorithms
best ts to this new Feature Selection approach. Thus, the contribution of this study is to
present a new approach for attribute selection, through a Semidynamic and a Dynamic
version, and determine which of the clustering methods performs better selection and get
a better performance in the construction of more accurate classifiers.


MEMBROS DA BANCA:
Presidente - 1350250 - ANNE MAGALY DE PAULA CANUTO
Interno - 2177445 - BRUNO MOTTA DE CARVALHO
Externo ao Programa - 1669545 - DANIEL SABINO AMORIM DE ARAUJO
Externo ao Programa - 4351681 - JOAO CARLOS XAVIER JUNIOR
Externo à Instituição - ADRIANA TAKAHASHI - UERN
Notícia cadastrada em: 09/02/2017 21:24
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