Multiclass Density Estimation Analysis in N-Dimensional Space featuring Delaunay Tessellation Field Estimation

Abstract: Multiclass density estimation is a method that can both estimate the density of a field and classify a given point to its targeted class. Delaunay Tessellation Field Estimation is a tessellation based multiclass density estimation technique that has recently been resurfaced and has been applied in the field of astronomy and computer science. In this paper Delaunay Tessellation Field Estimation is compared with other traditional density estimation techniques such as Kernel Density Estimation, k-Nearest Neighbour Density, Local Reachability Density and histogram to deliver a detailed performance analysis. One of the main conclusions is that Delaunay Tessellation Field Estimation scales in the number of data points but not the dimensions.