Introduction to Kernel Ridge Regression

place to kee notes, code, plots and pdf for my final project in kernel ridge regression

About:

This is a repo for my final project in Advanced Statistical Methods. The project intends to

• introduce non-linear regression
• explain Repreoducinng Kernel Hilbert Spaces, basis expansions, and its relationship to Kernel Ridge Regression
• explore a few simulated data sets with KRR
• disuss/execute parameter tuning in the context of generalizability and cross-validation.
• mention a few contexts in which KRR is used and discuss comparable models

Code:

Two primary packages are used: CVST and DRR. CVST allows for cross-validation via sequential testing. DRR allows for faster KRR via dimension reduction using a generalized PCA approach. Simulate data from CVST. Choose parameters: lambda and sigma.