Model Browser User's Guide

CenterExchange

This algorithm takes a concept from optimal Design of Experiments and applies it to the center selection problem in radial basis functions. A candidate set of centers is generated by a Latin hypercube, a method that provides a quasi-uniform distribution of points. From this candidate set, n centers are chosen at random. This set is augmented by p new centers, then this set of n+p centers is reduced to n by iteratively removing the center that yields the best PRESS statistic (as in stepwise). This process is repeated the number of times specified in Number of augment/reduce cycles.

This is the only algorithm that permits centers that are not located at the data points. The algorithm has the potential to be more flexible than the other center selection algorithms that choose the centers to be a subset of the data points; however, it is significantly more time-consuming and not recommended on larger problems.

Fit Parameters

Number of centers: The number of centers that will be chosen.

Number of augment/reduce cycles: The number of times that the center set is augmented, then reduced.

Number of centers to augment by: How many centers to augment by.

WiggleCenters

Lambda Selection Algorithms