Transductive Inference Based Multi Dimensional Neville Algorithm for Estimating Values of Functions
Lin Ma · 2005
An algorithm based on transductive inference learning used for estimating values of functions. It does not use any predefined modules and parameters and estimates the values of functions directly. It is the biggest difference between traditional algorithms for estimating values of functions. But the most trouble is how to implement the algorithm. Our paper discusses a transductive inference based multi dimensional Neville algorithm for estimating values of functions. By the use of projecting methods, we get multi dimensional Neville algorithm for estimating values of functions. The results of experiments show our algorithm not only successfully overcomes Runge problem of traditional algorithm for estimating values of functions, but also has a very nice function values estimating results and can be used in multi dimensional circumstance. We also provide some discussion of the selection of kernel parameters. Our algorithm shows a brand new way in transductive inference field.