Regularization: Intuition behind the math

Regularization in Machine Learning is talked about a lot, often indicating that it solves the high variance problem whilst also helping with feature selection. A model is said to have overfit some training data when the error on it is very low but the error on unseen data is very high. This is explained by the formula for variance. &#x003C3; 2 &#x0003D; 1 N &#x02211; i &#x0003D; 1 N &#x00028; x i…