Abstract: According to the fact that outlier points are the data that are inconsistent with most of data in a data set,and that boundary points are located on the edge of data area with different densities,an algorithm based on relative density was proposed to determine the outlier and boundary points.Through dividing the neighborhood area,which is centered by this point with a radius of r,into two semi-neighborhood areas,and determining this data point’s isolation level and boundary level based on the relative density of these semi-neighborhood areas with the original neighborhood area,a final judgment whether a data point is boundary or outlier point can be made according to the threshold value.Experimental results indicate that this algorithm can effectively and accurately identify the outlier and boundary points from multi-density data sets.

Key words: Neighborhood,Density,Isolation level,Outlier,Boundary level,Boundary points