---
title: "bias variance tradeoff"
source: https://www.jemoka.com/posts/kbhbias_variance_tradeoff/
---

Three models of fitting. Consider trying to fit some dataset \(|D|= n\) that&rsquo;s roughly quadratic with&hellip;
a linear model: underfit, high bias (i.e. &ldquo;model imposes bias of linearity on data&rdquo;) a nth order polynomial: overfit, high variance (i.e. &ldquo;a small perturbation of data brings lots of change&rdquo;) Its important to pay attention if you are having high bias of high variance&mdash;solutions of each is different from each other.
intuition of overfitting See overfit
diagnosing bias variance tradeoff problems Let&rsquo;s consider:
Reference Training Test Judgment 2% 2% 2% High Bias 10% 2.5% 10% High Variance 10% 10% 20% Both High Bias and Variance
