Memorias de investigación
Artículos en revistas:
A method for outlier detection based on cluster analysis and visual expert criteria
Año:2019
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications perform outlier detection, often as a preliminary step in order to filter out outliers and build more representative models. In this paper, we propose an outlier detection method based on a clustering process. The aim behind the proposal outlined in this paper is to overcome the specificity of many existing outlier detection techniques that fail to take into account the inherent dispersion of domain objects. The outlier detection method is based on four criteria designed to represent how human beings (experts in each domain) visually identify outliers within a set of objects after analysing the clusters. This has an advantage over other clustering?based outlier detection techniques that are founded on a purely numerical analysis of clusters. Our proposal has been evaluated, with satisfactory results, on data (particularly time series) from two different domains: stabilometry, a branch of medicine studying balance?related functions in human beings and electroencephalography (EEG), a neurological exploration used to diagnose nervous system disorders. To validate the proposed method, we studied method outlier detection and efficiency in terms of runtime. The results of regression analyses confirm that our proposal is useful for detecting outlier data in different domains, with a false positive rate of less than 2% and a reliability greater than 99%.
Internacional
Si
JCR del ISI
Si
Título de la revista
Expert Systems
ISSN
0266-4720
Factor de impacto JCR
1,505
Información de impacto
Volumen
DOI
10.1111/exsy.12473
Número de revista
Desde la página
49
Hasta la página
104
Mes
NOVIEMBRE
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Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software