org.apache.spark.streamdm.clusterers.utils

KMeans

object KMeans extends Serializable

The KMeans object computes the weighted k-means clustering given an array of Examples. It assumes that the inputs are weighted. Each instance will contribute a weight number of instances to the cluster.

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  8. def cluster(input: Array[Example], k: Int = 10, iterations: Int = 1000): Array[Example]

    Init the model based on the algorithm implemented in the learner, from the stream of instances given for training.

    Init the model based on the algorithm implemented in the learner, from the stream of instances given for training.

    input

    an Array of Example containing the instances to be clustered

    k

    the number of clusters (default 10)

    iterations

    the number of loops of k-means (default 1000)

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