Oversampling and undersampling in data analysis
id:
oversampling-and-undersampling-in-data-analysis-161-4918142
title:
Oversampling and undersampling in data analysis
text:
Within statistics, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set. These terms are used both in statistical sampling, survey design methodology and in machine learning. Oversampling and undersampling are opposite and roughly equivalent techniques. There are also more complex oversampling techniques, including the creation of artificial data points with algorithms like Synthetic minority oversampling technique.
brand slug:
wiki
category slug:
encyclopedia
description:
Statistical sampling techniques
original url:
https://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis
date created:
2009-03-23T13:22:15Z
date modified:
2024-08-27T04:42:06Z
main entity:
{"identifier":"Q7113891","url":"https://www.wikidata.org/entity/Q7113891"}
image:
fields total:
13
integrity:
15