Introduction to Regularization

Understand the difference between underfitting and overfitting, as well as the necessity and use of regularization.

Let's start with understanding the difference between underfitting and overfitting.

Underfitting vs. overfitting

Let's say we have the following plots (shown below):

  • Left plot: Underfitted model with low accuracy score (R-squared) and higher error (SSE: sum of squared error).

  • Middle plot: Model with average accuracy score and error. Can this be improved?

  • Right plot: The overfitted model has a very high accuracy score and low error (practically R-squared = 1 and SSE = 0 since the fitted line passes through all the data points).

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