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Related Questions
- What are the common distance metrics used in clustering algorithms and how do they differ in high-dimensional data?
- How does the choice of distance metric affect the stability of clustering results in high-dimensional data?
- Can you explain the impact of distance metric on the interpretability of clustering results in terms of feature importance and dimensionality reduction?
- How does the choice of distance metric influence the clustering algorithm's ability to capture non-linear relationships in high-dimensional data?
- What are the implications of using a distance metric that is sensitive to outliers on the interpretability of clustering results in high-dimensional data?
- Can you discuss the trade-off between using a distance metric that preserves global structure and one that preserves local structure in high-dimensional data?
- How does the choice of distance metric affect the clustering algorithm's ability to handle noisy and missing data in high-dimensional data?
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