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Application of the Variable Precision Rough Sets Model to Estimate the Outlier Probability of Each Element
Joint Authors
Maciá-Pérez, Francisco
Martienz, Jose Vicente Berna
Oliva, Alberto Fernández
Ortega, Miguel Abreu
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-08
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
In a data mining process, outlier detection aims to use the high marginality of these elements to identify them by measuring their degree of deviation from representative patterns, thereby yielding relevant knowledge.
Whereas rough sets (RS) theory has been applied to the field of knowledge discovery in databases (KDD) since its formulation in the 1980s; in recent years, outlier detection has been increasingly regarded as a KDD process with its own usefulness.
The application of RS theory as a basis to characterise and detect outliers is a novel approach with great theoretical relevance and practical applicability.
However, algorithms whose spatial and temporal complexity allows their application to realistic scenarios involving vast amounts of data and requiring very fast responses are difficult to develop.
This study presents a theoretical framework based on a generalisation of RS theory, termed the variable precision rough sets model (VPRS), which allows the establishment of a stochastic approach to solving the problem of assessing whether a given element is an outlier within a specific universe of data.
An algorithm derived from quasi-linearisation is developed based on this theoretical framework, thus enabling its application to large volumes of data.
The experiments conducted demonstrate the feasibility of the proposed algorithm, whose usefulness is contextualised by comparison to different algorithms analysed in the literature.
American Psychological Association (APA)
Maciá-Pérez, Francisco& Martienz, Jose Vicente Berna& Oliva, Alberto Fernández& Ortega, Miguel Abreu. 2018. Application of the Variable Precision Rough Sets Model to Estimate the Outlier Probability of Each Element. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134411
Modern Language Association (MLA)
Maciá-Pérez, Francisco…[et al.]. Application of the Variable Precision Rough Sets Model to Estimate the Outlier Probability of Each Element. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1134411
American Medical Association (AMA)
Maciá-Pérez, Francisco& Martienz, Jose Vicente Berna& Oliva, Alberto Fernández& Ortega, Miguel Abreu. Application of the Variable Precision Rough Sets Model to Estimate the Outlier Probability of Each Element. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1134411
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1134411