When solving problems using machine learning there is typically a relationship between errors within training sets, errors within testing sets and model complexity. This relationship and the arrival at an optimum trade off between model variance and bias is commonly denoted the bias-variance trade off. Today we are going to talk about the bias-variance tradeoff […]