Sample complexity
id:
sample-complexity-166-2028997
title:
Sample complexity
text:
The sample complexity of a machine learning algorithm represents the number of training-samples that it needs in order to successfully learn a target function. More precisely, the sample complexity is the number of training-samples that we need to supply to the algorithm, so that the function returned by the algorithm is within an arbitrarily small error of the best possible function, with probability arbitrarily close to 1. There are two variants of sample complexity:
- The weak variant fixes
brand slug:
wiki
category slug:
encyclopedia
description:
Attribute of machine learning models
original url:
https://en.wikipedia.org/wiki/Sample_complexity
date created:
2014-07-10T21:29:15Z
date modified:
2024-08-29T15:26:33Z
main entity:
{"identifier":"Q18354077","url":"https://www.wikidata.org/entity/Q18354077"}
image:
fields total:
13
integrity:
15