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The document discusses the mathematical foundations of splines and penalization in regression analysis, highlighting the limitations of Ordinary Least Squares (OLS) models in capturing non-linear patterns. It explains the use of regression splines, including piecewise linear and cubic splines, and introduces penalized regression techniques like Ridge and LASSO, which help manage the bias-variance trade-off. Additionally, it covers the Elastic Net method, which addresses multicollinearity issues by combining
- Author
- sidikhalid86
- Language
- EN