5 Major Evaluation Metrics for Clustering
Evaluation metrics for clustering are used to assess the quality and performance of clustering algorithms. Here are some commonly used evaluation metrics for clustering: Silhouette coefficient: This metric measures how well each data point fits into its assigned cluster and ranges from -1 to 1. A high silhouette coefficient indicates that the data points are well-clustered, while a low coefficient indicates that the data points may be assigned to the wrong cluster. I would…
5 Major Evaluation Metrics for Clustering Evaluation metrics for clustering are used to assess the quality and performance of clustering algorithms. Here are some commonly used evaluation metrics for clustering: Silhouette coefficient: This metric measures how well each data point fits into its assigned cluster and ranges from -1 to 1. A high silhouette coefficient indicates that the data points are well-clustered, while a low coefficient indicates that the data points may be assigned to the wrong cluster. I would… nlp
5 Major Evaluation Metrics Clustering Evaluation metric clustering used ass quality performance clustering algorithm commonly used evaluation metric clustering Silhouette coefficient metric measure well data point fit assigned cluster range 1 1 high silhouette coefficient indicates data point wellclustered low coefficient indicates data point may assigned wrong cluster would… nlp