<ul data-eligibleForWebStory="false"><li>Clustering is crucial in data-driven fields, but accuracy is challenging especially in large datasets.</li><li>A new method, CAS (Condensed and Accelerated Silhouette), aims to find the optimal k in K-Means clustering efficiently.</li><li>The approach combines multiple techniques and statistical methods for better performance in text and image data clustering.</li><li>Experimental results indicate significant improvements in computational efficiency and cluster validity compared to traditional methods.</li></ul>

CAS Condensed and Accelerated Silhouette: An Efficient Method for Determining the Optimal K in K-Means Clustering

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