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[SPARK-24628][DOC]Typos of the example code in docs/mllib-data-types.md #21612

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[SPARK-24628][DOC]Typos of the example code in docs/mllib-data-types.md #21612

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If you want to create a dense matrix ((1.0, 2.0), (3.0, 4.0), (5.0, 6…
huangweizhe123 Jun 22, 2018
6c28df4
The MatrixEntry here is supposed to be MatrixEntry(2, 1, 3.7)
huangweizhe123 Jun 25, 2018
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4 changes: 2 additions & 2 deletions docs/mllib-data-types.md
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Expand Up @@ -317,7 +317,7 @@ Refer to the [`Matrix` Python docs](api/python/pyspark.mllib.html#pyspark.mllib.
from pyspark.mllib.linalg import Matrix, Matrices

# Create a dense matrix ((1.0, 2.0), (3.0, 4.0), (5.0, 6.0))
dm2 = Matrices.dense(3, 2, [1, 2, 3, 4, 5, 6])
dm2 = Matrices.dense(3, 2, [1, 3, 5, 2, 4, 6])

# Create a sparse matrix ((9.0, 0.0), (0.0, 8.0), (0.0, 6.0))
sm = Matrices.sparse(3, 2, [0, 1, 3], [0, 2, 1], [9, 6, 8])
Expand Down Expand Up @@ -624,7 +624,7 @@ from pyspark.mllib.linalg.distributed import CoordinateMatrix, MatrixEntry

# Create an RDD of coordinate entries.
# - This can be done explicitly with the MatrixEntry class:
entries = sc.parallelize([MatrixEntry(0, 0, 1.2), MatrixEntry(1, 0, 2.1), MatrixEntry(6, 1, 3.7)])
entries = sc.parallelize([MatrixEntry(0, 0, 1.2), MatrixEntry(1, 0, 2.1), MatrixEntry(2, 1, 3.7)])
# - or using (long, long, float) tuples:
entries = sc.parallelize([(0, 0, 1.2), (1, 0, 2.1), (2, 1, 3.7)])

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