Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10610#discussion_r51298395
--- 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
--- End diff --
Sure, I'll make sure to verify this with the Sphinx output
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