Given an unlabeled dataset {x(1),...,x(m)}. The K-mean algorithm has been run with 40 different random initializations, and 40 different clusterings of the data have been Ex0 – µwl² to choose the best obtained. Describe how we should use m m clustering.
Given an unlabeled dataset {x(1),...,x(m)}. The K-mean algorithm has been run with 40 different random initializations, and 40 different clusterings of the data have been Ex0 – µwl² to choose the best obtained. Describe how we should use m m clustering.
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![Given an unlabeled dataset {x(1),...,x(m)}. The K-mean algorithm has been run with
40 different random initializations, and 40 different clusterings of the data have been
Ex0 – µwl² to choose the best
obtained. Describe how we should use
m
m
clustering.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa09f8c30-0603-48d9-872e-02479fd10c93%2F3464589f-8845-44c4-bd13-5cf38c788ec1%2F71mt5vl_processed.png&w=3840&q=75)
Transcribed Image Text:Given an unlabeled dataset {x(1),...,x(m)}. The K-mean algorithm has been run with
40 different random initializations, and 40 different clusterings of the data have been
Ex0 – µwl² to choose the best
obtained. Describe how we should use
m
m
clustering.
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