Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/10610#discussion_r51214338 --- Diff: python/pyspark/mllib/clustering.py --- @@ -448,18 +508,24 @@ class PowerIterationClustering(object): @since('1.5.0') def train(cls, rdd, k, maxIterations=100, initMode="random"): """ - :param rdd: an RDD of (i, j, s,,ij,,) tuples representing the - affinity matrix, which is the matrix A in the PIC paper. - The similarity s,,ij,, must be nonnegative. - This is a symmetric matrix and hence s,,ij,, = s,,ji,,. - For any (i, j) with nonzero similarity, there should be - either (i, j, s,,ij,,) or (j, i, s,,ji,,) in the input. - Tuples with i = j are ignored, because we assume - s,,ij,, = 0.0. - :param k: Number of clusters. - :param maxIterations: Maximum number of iterations of the - PIC algorithm. - :param initMode: Initialization mode. + :param rdd: + Train with a RDD of (i, j, s,,ij,,) tuples representing the + affinity matrix, which is the matrix A in the PIC paper. The + similarity s,,ij,, must be nonnegative. This is a symmetric + matrix and hence s,,ij,, = s,,ji,,. For any (i, j) with + nonzero similarity, there should be either (i, j, s,,ij,,) or + (j, i, s,,ji,,) in the input. Tuples with i = j are ignored, + because we assume s,,ij,, = 0.0. + :param k: + Number of clusters. + :param maxIterations: + Maximum number of iterations of the PIC algorithm. + (default: 100) + :param initMode: + Set the initialization mode. This can be either "random" to use --- End diff -- Remove `Set`.
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