# Why use regularization?

In a linear model, regularization decreases the slope. Do we just assume that fitting a lin model on training data overfits by almost always creating a slope which is higher than it would be with infinite observations instead? What is the intuition?

y = x_1 + eps*(x_2 + ... + x_100)