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Reference.org
Oversampling and undersampling in data analysis
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<p>Within <a href="/facts/Statistics/DNPsKGYU">statistics</a>, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a <a href="/facts/Data_set/eDvegUTK">data set</a> (i.e. the ratio between the different classes/categories represented). These terms are used both in statistical sampling, survey design methodology and in <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a>. </p><p>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. </p>