Model Selection: Underfitting, Overfitting, and the Bias-Variance Tradeoff
The material in this post has been migrated with python implementations to my github pages website.
Posted on April 21, 2013, in Regression, Simulations, Statistics, Theory and tagged bias-variance decomposition, bias-variance tradeoff, dependent variable, estimator, estimator bias, estimator variance, independent variable, learning curve, polyfit.m, polynomial model, Regression, Simulation, testing error, testing set, training error, training set. Bookmark the permalink. 10 Comments.