The Bias-Variance Tradeoff

A critical concept in machine learning

The bias-variance tradeoff is widely considered a critical concept in machine learning. The most valuable machine learning models can produce accurate predictions on new, unseen data. As a machine learning practitioner, crafting valuable models requires carefully balancing the bias-variance tradeoff.

This lesson builds on the knowledge of underfitting and overfitting to understand the bias-variance tradeoff. Tuning models for the bias-variance tradeoff using the cross-validation technique will be covered later in the course.

The dart throwing analogy

An intuitive way to learn the bias-variance tradeoff is by using the analogy of throwing darts at a dartboard. To make this analogy relatable, consider a hypothetical dart enthusiast named Bob.

Bob is an avid participant in dart throwing competitions and has decided to improve his skill. To allow himself ample time to practice, Bob ...