Nonlinear Regression and Regularization in Data Mining - Spring 2023

Learn about advanced regression techniques in this comprehensive data mining lecture that progresses from linear regression fundamentals to complex nonlinear methods and regularization approaches. Begin with a quick review of linear regression before diving into nonlinear regression concepts, including practical Python implementations and various nonlinear mapping examples. Explore polynomial regression unification, feature space mapping, and optimization techniques for nonlinear models. Address critical machine learning challenges like underfitting and overfitting through cross-validation methods. Conclude with an in-depth examination of regularization principles, different types of regularized regression models, and specific solutions for ridge regression problems.