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What is Understanding Clustering in Machine Learning about?

Clustering is the process of grouping data points into subsets (clusters) based on shared traits, emphasizing high intra-class similarity and low inter-class similarity. It is an unsupervised learning technique used in various applications such as marketing, fraud detection, and city planning, with methods including K-means and K-medoids. The effectiveness of clustering depends on the chosen distance measures and the algorithm

Author

Shivani Samdani

Language

EN