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What is the advantage of standardizing / normalizing the data before running the K - means algorithm? It sets the mean of the scaled components

What is the advantage of standardizing

/

normalizing the data before running the

K -

means algorithm?

It sets the mean of the scaled components to

1 .

It allows you to identify cluster centers.

It makes variances equal for each component.

It reveals the cluster membership of each point.

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