Efficient Computation of Complex Distance Metrics Using Hierarchical Filtering

By their very nature, memory based algorithms such as KNN or Parzen windows require a computationally expensive search of a large database of prototypes. In this paper we optimize the searching processfor tangent distance (Simard, LeCun and Denker, 1993) to improve speed performance. The closest prototypes are found by recursively searching included subset.s of the database using distances ofincreasing complexit.y. This is done by using a hierarchy of tangent distances (increasing the Humber of tangent.