Understanding your performance metrics for clustering

#artificialintelligence 

Clustering is categorized under unsupervised learning, which forms the niche part of machine learning. Unlike supervised learning which is more common in most common machine learning study, classification tasks learn from the provided labeled data and makes class predictions. However, this does not cause the clustering method to be less desirable, as clustering algorithms are essential in discovering unexplored insights. Thus, it is important to understand the performance of the clustering task and to decide whether the clusters formed are trustable. Silhouette Analysis is the most common method as it is more straightforward compared to others.

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