(a) Compare the various constraint based clustering methods.
Explanation
Constraint-based clustering methods are useful for discovering clusters with specific properties. They are robust to noise and outliers and can handle high-dimensional data. However, they can suffer from the curse of dimensionality and require careful parameter tuning.
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