When using K means, why might different runs produce slightly different results It relies on random initialization It scales the data on each iteration It uses a different central tendency measure for computing cluster centroids in each iteration It uses a different distance metrics on each iteration

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When using K means, why might different runs produce slightly different results  It relies on random initialization It scales the data on each iteration It uses a different central tendency measure for computing cluster centroids in each iteration It uses a different distance metrics on each iteration

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Question: When using K-means, why might different runs produce slightly different results? It relies on random initialization It scales the data on each iteration It uses

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