How does K-Means clustering respond to non-spherical data distributions, and how can initialization affect this?
- Adapts well to non-spherical data
- Performs equally well with all data shapes
- Struggles with non-spherical data; Initialization can alleviate this
- Struggles with non-spherical data; Initialization has no effect
K-Means tends to struggle with non-spherical data distributions since it relies on Euclidean distance. Careful initialization can partially alleviate this issue but cannot fully overcome the fundamental limitation.
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