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Related Questions
- What are the common distance metrics used in clustering algorithms and how do they affect the clustering results?
- How does the choice of distance metric impact the robustness of a clustering algorithm to noisy data?
- Can you explain the concept of 'sensitivity to noise' in clustering and how distance metrics contribute to it?
- How do different distance metrics influence the detection of outliers in clustering algorithms?
- What is the relationship between the choice of distance metric and the clustering algorithm's ability to handle high-dimensional data?
- Can you provide examples of scenarios where a specific distance metric is more suitable than others for clustering?
- How does the choice of distance metric affect the interpretability of clustering results, particularly in terms of feature importance?
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