Bedregal, Benjamin René CallejasMoura, Ronildo Pinheiro de Araújo2014-12-172014-11-272014-12-172014-02-21MOURA, Ronildo Pinheiro de Araújo. An interval fuzzy clustering and validation index for clusteinf in interval symbolic data. 2014. 98 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal do Rio Grande do Norte, Natal, 2014.https://repositorio.ufrn.br/jspui/handle/123456789/18111Symbolic Data Analysis (SDA) main aims to provide tools for reducing large databases to extract knowledge and provide techniques to describe the unit of such data in complex units, as such, interval or histogram. The objective of this work is to extend classical clustering methods for symbolic interval data based on interval-based distance. The main advantage of using an interval-based distance for interval-based data lies on the fact that it preserves the underlying imprecision on intervals which is usually lost when real-valued distances are applied. This work includes an approach allow existing indices to be adapted to interval context. The proposed methods with interval-based distances are compared with distances punctual existing literature through experiments with simulated data and real data intervalapplication/pdfAcesso AbertoMatemática intervalar. Agrupamento de dados. Análise de dados simbólicos. Fuzzy c-Means. Distância intervalarInterval mathematics. Clustering. Symbolic data analysis. Fuzzy c-Means i-metricsmasterThesisCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO