How to fit a ridge-regression model with the application of a QCQP-Solver (MATLAB, library: yaLMIp)
This is the main-source code for a simple paper that I wrote.
The paper shows a typical task-setting from the field of operations research which is the basis for an example of how to fit a ridge regression model with the application of a QCQP-Solver.
The idea arose from a student-project within the lecture "Numerical Optimization" which is frequently held at the University of Freiburg.
The numeric data-vectors which are being used were created artificially. The correspondent command lines that were utilized to create the data are presented in the appendix.
Highlights are: -high-dimensional numeric data-vectors (dimension 185) -non-linear data-vector transformation -transformation of a QP into a QCQP with arguments of convergence and arguments of SVD -application of a QCQP-solver (yaLMIp).