Non-Deterministic Outlier Detection Method Based on the Variable Precision Rough Set Model

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 thegeneralisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of thisstudy is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degreeof uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison ofthe results with the RSBM-based method demonstrate the effectiveness of the method as well as the algorithm’s efficiency in diverse contexts, which alsoinvolve large amounts of data.