Statistically speaking the nonlinear regression is a kind of regression analysis for estimating the relationships between one or more independent variables in a nonlinear combination.
In this chapter, we will use the Python library
mlpy and its Kernel ridge regression implementation. We can find more information about nonlinear regression methods at http://mlpy.sourceforge.net/docs/3.3/nonlin_regr.html.
The most basic algorithm that can be kernelized is Kernel ridge regression (KRR). It is similar to an SVM (Support Vector Machines) (see Chapter 8, Working with Support Vector Machines) but the solution depends on all the training samples and not on the subset of support vectors. KRR works well with few ...