Homogeneity

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Creator

Created

Created

2025 Mar 11 11:25

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Editor

Edited

Edited

2025 Mar 11 11:30

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Heterogeneity

Class entropy

H(C) = -\sum_{c=1}^{|C|} \frac{n_c}{n} \log \frac{n_c}{n}

Conditional entropy upon class

H(C|K) = -\sum_{k=1}^{|K|} \frac{n_k}{n} \sum_{c=1}^{|C|} \frac{n_{c,k}}{n_k} \log \frac{n_{c,k}}{n_k}

Homogeneity

\text{Homogeneity} = 1 - \frac{H(C|K)}{H(C)}

Homogeneity and heterogeneity (statistics)

In statistics, homogeneity and its opposite, heterogeneity, arise in describing the properties of a dataset, or several datasets. They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies (see also Study heterogeneity).

Homogeneity and heterogeneity (statistics)

https://en.wikipedia.org/wiki/Homogeneity_and_heterogeneity_(statistics)

Backlinks

Entropy Entropy Dissimilarity metrics V-measure Data Clustering

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