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What is Optimal Clusters in Data Analysis about?

The project aims to determine the optimal number of clusters in data using clustering analysis methods. Three methods were employed: the Elbow Method, Gap Statistics, and Bayesian Information Criterion, all suggesting that the optimal number of clusters is 3. The analysis highlights the limitations of using only these methods and acknowledges that different approaches may yield slightly varying results.

Author

gonguntladeepika30

Language

EN