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Related Questions
- How does the choice of distance metric impact the clustering of high-dimensional data?
- Can you explain the differences between Euclidean, Manhattan, and cosine distance metrics in clustering?
- How does the choice of distance metric affect the stability of clustering results?
- What are the implications of using a non-Euclidean distance metric in clustering, such as the Minkowski distance?
- How does the choice of distance metric impact the performance of clustering algorithms on real-world datasets?
- Can you discuss the trade-offs between using a simple distance metric versus a more complex one, such as the Mahalanobis distance?
- How does the choice of distance metric affect the interpretability of clustering results?
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