The Calinski-Harabasz Index, also known as the Variance Ratio Criterion, is a metric used to evaluate the quality of clustering results in machine learning. It measures the ratio of the sum of between-cluster dispersion to within-cluster dispersion, where higher values indicate better-defined clusters. This index is essential for determining the optimal number of clusters in terahertz data analysis, helping to ensure that the data is grouped effectively for further interpretation and analysis.
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