If I understand what you meant by "dimensional scaling" correctly, then you probably want to do some sort of nonlinear projection, i.e., projection of high dimensional data to a low dimensional nonlinear surface using neural networks.
There have been several attempts to do that such as nonlinear PCA based on three-hidden layered neural networks. The hidden nodes at the middle layer can be used as nonlinear principal components. But from my personal experience, training such big neural networks is not easy problem esp. when the dimension of input data is higher than 4~50. Hope this would help, Jay Liu . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
