Projection Pursuit Regression And Neural Networks. As we make clear in this section they are just nonlinear statistical models much like the projection pursuit regression model discussed above. A Comparison of Projection Pursuit and Neural Network Regression Modeling.
Feed forward neural networks are compared with standard and new statistical classification procedures for the classification of proteins. Both projection pursuit regression and neural networks models project the input vector onto a one-dimensional hyperplane and then applies a nonlinear transformation of the input variables that are then added in a linear fashion. Jan 01 1994 Jones L.
May 01 1992 Two types of feedforward network learning methods for model-free regression problems are studied and compared in this paper.
Pursuit Regression with Application to Neural Networks Nathan Intrator Institute for Brain and Neural Systems Brown University Box 1843 Providence NO291 2 USA We present a novel classification and regression method that com- bines exploratory projection pursuit unsupervised training with pro-. A learning method developed in different fields statistics and artificial intelligence. Jan 01 1994 Jones L. Projection pursuit regression and kernel regression are methods for estimating a smooth function of several variables from noisy data obtained at scattered sites.
