calinski harabasz score
时间: 2023-09-24 07:08:07 浏览: 30
Calinski-Harabasz score, also known as Variance Ratio Criterion, is a metric used for evaluating the quality of clustering in data analysis. The score measures the ratio of between-cluster variance to within-cluster variance. A higher score indicates better separation between the clusters.
The formula for Calinski-Harabasz score is: CH = (SSB/(k-1)) / (SSW/(n-k)), where SSB is the between-cluster sum of squares, SSW is the within-cluster sum of squares, k is the number of clusters, and n is the total number of data points.
In general, a higher CH score indicates better separation between the clusters, but the optimal number of clusters should be determined by comparing CH scores across different cluster solutions.
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