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in Machine Learning by (120 points)
As we know the classification algorithms work as supervised learning in which the target data are known, on the other hand, the clustering algorithms work as unsupervised learning in which the target data are unknown.

When we evaluated the results of both methods in terms of the f-measure metric, we notice that the clustering results are less than classification results. So, please what is the reason and if there is a reference that proves my approach please put it here.

hank you.

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