Article
External clustering validity index based on chi-squared statistical test
Author/s | Luna Romera, José María
Martínez Ballesteros, María del Mar García Gutiérrez, Jorge Riquelme Santos, José Cristóbal |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2019 |
Deposit Date | 2022-04-13 |
Published in |
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Awards | Premio Mensual Publicación Científica Destacada de la US. Escuela Técnica Superior de Ingeniería Informática |
Abstract | Clustering is one of the most commonly used techniques in data mining. Its main goal is
to group objects into clusters so that each group contains objects that are more similar to
each other than to objects in other ... Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so that each group contains objects that are more similar to each other than to objects in other clusters. The evaluation of a clustering solution is a task carried out through the application of validity indices. These indices measure the quality of the solution and can be classified as either internal that calculate the quality of the solution through the data of the clusters, or as external indices that measure the quality by means of external information such as the class. Generally, indices from the literature determine their optimal result through graphical representation, whose results could be imprecisely interpreted. The aim of this paper is to present a new external validity index based on the chi-squared statistical test named Chi Index, which presents accurate results that require no further interpretation. Chi Index was analyzed using the clustering results of 3 clustering methods in 47 public datasets. Results indicate a better hit rate and a lower percentage of error against 15 external validity indices from the literature. |
Funding agencies | Ministerio de Economía y Competitividad (MINECO). España |
Project ID. | TIN2014-55894-C2-R
TIN2017-88209-C2-2-R |
Citation | Luna Romera, J.M., Martínez Ballesteros, M.d.M., García Gutiérrez, J. y Riquelme Santos, J.C. (2019). External clustering validity index based on chi-squared statistical test. Information Sciences, 487 (June 2019), 1-17. |
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