bias-variance decomposition

(55 minutes to learn)

Summary

The bias-variance decomposition (often referred to as the bias-variance tradeoff) is a frequentist analysis of the generalization capability of an estimator, i.e. a learning algorithm.

Context

This concept has the prerequisites:

Core resources (read/watch one of the following)

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Supplemental resources (the following are optional, but you may find them useful)

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Mathematical Monk: Machine Learning (2011)
Online videos on machine learning.
The Elements of Statistical Learning
A graudate-level statistical learning textbook with a focus on frequentist methods.
Authors: Trevor Hastie,Robert Tibshirani,Jerome Friedman

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See also