Alberto Fernández Oliva1, Francisco Maciá Pérez2, José Vicente Berná-Martinez2,*, Miguel Abreu Ortega3
Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131
Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the
generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this
study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree
of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of
the results with… More >
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