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evaluating clustering algorithms?
We are working on text clustering for the data science project we find a few algorithms that can work with text like
-K-means
-K-medoids
These two are centroid clustering and we use Davies Bouldin evaluation metrics to evaluate them
-Agglomerative clustering
-Top-down clustering
These two are hierarchical clustering but we don't know how to evaluate them we need to compare between these four, so we need to find unified evaluation method
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