Sample complexity: Difference between revisions

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{{Machine learning bar}}

In [[machine learning]], '''sample complexity''' is the number of examples needed for the estimate of a target function to be within a given error rate.<ref name = "Balcan">{{cite doijournal | doi = 10.1007/s10994-010-5174-y | title=The true sample complexity of active learning | journal=Machine Learning | date=2010 | volume=80 | issue=2-3 | pages=111–139 | first=Maria-Florina | last=Balcan}}</ref> The '''sample complexity''' of a machine learning algorithm characterizes its rate of [[consistency (statistics)|consistency]].

==Mathematical Setup==