You have a dataset with a clear elbow point, but the K-Means clustering is still not performing well. How could centroid initialization be contributing to this issue?
- Centroids initialized too far from the data
- Centroids initialized within one cluster
- Initializing centroids based on mean
- Poor centroid initialization causing slow convergence
Poor centroid initialization can cause slow convergence or convergence to suboptimal solutions, even when there is a clear elbow point. This leads to the K-Means clustering not performing as well as it should.
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