A brief note on how bias and variance makes a model as Underfitted or Generalized or Overfitted!

In this post, instead of writing so many paragraphs I just made an info-graphic for ease of understanding.

Underfitted — Generalized — Overfitted

Underfitted:

A model could fit the training and testing data very poorly (high bias and low variance) — left most graph in above Info-graphic. This is known as underfitted.

Overfitted:

A modelcan fit the training data very well and the testing data very poorly. (low bias and high variance) — Right most graph in above Info-graphic. This is known as overfitted.

#underfitting #bias #machine-learning #overfitting #variance #deep learning