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Related Questions
- Can you explain how different distance metrics can affect the interpretability of clustering results in unsupervised learning?
- How do different distance metrics impact the visual representation of clusters in dimensionality-reduced spaces?
- What are the implications of using Euclidean distance versus cosine similarity in clustering tasks?
- Can you discuss the effect of different distance metrics on the quality of clustering results in high-dimensional data?
- How can we evaluate and compare the performance of different distance metrics in clustering tasks?
- What role does the choice of distance metric play in the sensitivity of clustering algorithms to noise and outliers?
- Can you describe the advantages and disadvantages of using Mahalanobis distance versus standard Euclidean distance in clustering?
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