RBF networks for regression



Radial basis function are a simple, fast method for universal function approximation / regression. The idea is to find a mapping X->y where X and y are continuous real variables. The mapping is linear over features of X: y=rbfWeight*features(X). The features are of the form:

f_j(x) = exp(-||x-mu_j||_2^2 / 2 sig_j^2 ).

Wavelet Support Vector Regression (WSVR)




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SKU: P2018F224 Category: