Description: K-means algorithm accept parameter k Then will the n of prior input data object is divided into k clustering to make won clustering meet: the same clustering the object in the similarity is higher And different clustering the object in the smaller similarity. Clustering similarity is using the cluster of the object in the mean gained a "center object" (the center of gravity) to calculate.
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