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Focusing on clustering methods, the book explores both classical and modern techniques, including K-Means and divisive clustering. Enhanced case studies illustrate practical applications, while the second edition introduces new topics such as variable selection, similarity data clustering, and spectral clustering. Additionally, it offers resources through a dedicated website featuring MATLAB code and datasets for the examples discussed, making it a comprehensive guide for understanding and implementing clustering techniques.
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Clustering, Boris Mirkin
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- Released
- 2019
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- (Paperback)
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