Summary of Generalized Linear Models Tutorial 2 Video 2

Overfitting can occur in linear regression and logistic regression models when there is less data and more features.

Notable Quotes

01:30 — « To overcome overfitting issue, people use regularization. »
01:42 — « It shrinks the parameter theta in GLMs towards zero. Thus, it can reduce overfitting. »
02:39 — « So one intuitive way of improving the parameter estimate is to suppress these large theta values. »
02:55 — « Formally written as this. We add a penalty term to the log-likelihood, maximizing the log likelihood, L prime, will lead to minimizing the magnitude of theta i. »
05:02 — « Another popular regularization is L1 regularization, which is also known as Lasso regularization. »

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Educational

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