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Related Questions
- What are the advantages and disadvantages of using Euclidean distance in k-means clustering?
- How does the choice of distance measure impact the cluster density and separation in k-means clustering?
- What are the effects of using Manhattan distance or Minkowski distance on k-means clustering stability and interpretability?
- Can you explain how to choose the optimal distance measure for k-means clustering based on the characteristics of the data?
- How does the k-means clustering algorithm handle categorical data, and what distance measures are commonly used for such data?
- What are the differences in clustering results when using k-means with different distance measures, such as Euclidean, Manhattan, and cosine similarity?
- How can the selection of distance measure affect the identification of outliers and anomalies in k-means clustering?
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