Mean Purity Score

**Mean Purity Score**

The **Mean Purity Score** is a statistical metric commonly used in clustering analysis to evaluate the quality of the resulting clusters. It measures how well clusters correspond to the ground truth classes by calculating the average of the highest class proportions within each cluster. A higher mean purity score indicates that clusters are more homogeneous and accurately represent the underlying categories. This tag is useful for posts discussing data science, machine learning, cluster evaluation, and performance metrics.