GROUT-A Grid Approximation-based Algorithm for Outlier Detection in Large Dataset

This paper presents a novel approach for outlier detection with high efficiency both in memory and time usage.By revealing the key features of the outlier detection task and the realworld dataset,an analytical definition of outlier is given followed by a grid approximationbased detection algorithm ″GROUT″.Results of experimental studies on realworld and synthetic datasets demonstrate promising behaviour of our approach.