SPARK-6454 [DOCS] Fix links to pyspark api

Author: Kamil Smuga <smugakamil@gmail.com>
Author: stderr <smugakamil@gmail.com>

Closes #5120 from kamilsmuga/master and squashes the following commits:

fee3281 [Kamil Smuga] more python api links fixed for docs
13240cb [Kamil Smuga] resolved merge conflicts with upstream/master
6649b3b [Kamil Smuga] fix broken docs links to Python API
92f03d7 [stderr] Fix links to pyspark api

1 files changed, 4 insertions, 4 deletions

diff --git a/docs/mllib-data-types.md b/docs/mllib-data-types.md
index fe6c1bf7bf..4f2a2f7104 100644
--- a/docs/mllib-data-types.md
+++ b/docs/mllib-data-types.md
@@ -78,13 +78,13 @@ MLlib recognizes the following types as dense vectors:
 
 and the following as sparse vectors:
 
-* MLlib's [`SparseVector`](api/python/pyspark.mllib.linalg.SparseVector-class.html).
+* MLlib's [`SparseVector`](api/python/pyspark.mllib.html#pyspark.mllib.linalg.SparseVector).
 * SciPy's
   [`csc_matrix`](http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csc_matrix.html#scipy.sparse.csc_matrix)
   with a single column
 
 We recommend using NumPy arrays over lists for efficiency, and using the factory methods implemented
-in [`Vectors`](api/python/pyspark.mllib.linalg.Vectors-class.html) to create sparse vectors.
+in [`Vectors`](api/python/pyspark.mllib.html#pyspark.mllib.linalg.Vector) to create sparse vectors.
 
 {% highlight python %}
 import numpy as np
@@ -151,7 +151,7 @@ LabeledPoint neg = new LabeledPoint(1.0, Vectors.sparse(3, new int[] {0, 2}, new
 <div data-lang="python" markdown="1">
 
 A labeled point is represented by
-[`LabeledPoint`](api/python/pyspark.mllib.regression.LabeledPoint-class.html).
+[`LabeledPoint`](api/python/pyspark.mllib.html#pyspark.mllib.regression.LabeledPoint).
 
 {% highlight python %}
 from pyspark.mllib.linalg import SparseVector
@@ -211,7 +211,7 @@ JavaRDD<LabeledPoint> examples =
 </div>
 
 <div data-lang="python" markdown="1">
-[`MLUtils.loadLibSVMFile`](api/python/pyspark.mllib.util.MLUtils-class.html) reads training
+[`MLUtils.loadLibSVMFile`](api/python/pyspark.mllib.html#pyspark.mllib.util.MLUtils) reads training
 examples stored in LIBSVM format.
 
 {% highlight python %}