Purity Score

**Purity Score**

The Purity Score is a metric used to evaluate the clarity and quality of classification results in data analysis and machine learning. It measures how well the clusters or groups in a dataset correspond to the true class labels, with higher scores indicating more accurate and distinct groupings. Often applied in clustering validation, the Purity Score helps assess the effectiveness of algorithms in segregating data into meaningful categories. Use this tag for posts related to data clustering, classification performance, and evaluation metrics.