address review comments

Author: wangmiao1981

docs/ml-clustering.md

@@ -153,7 +153,7 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.clustering.
 
 A [Gaussian Mixture Model](http://en.wikipedia.org/wiki/Mixture_model#Multivariate_Gaussian_mixture_model)
 represents a composite distribution whereby points are drawn from one of *k* Gaussian sub-distributions,
-each with its own probability. The spark.ml implementation uses the
+each with its own probability. The `spark.ml` implementation uses the
 [expectation-maximization](http://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm)
 algorithm to induce the maximum-likelihood model given a set of samples.
 
@@ -208,7 +208,6 @@ model.
   </tbody>
 </table>
 
-
 ### Example
 
 <div class="codetabs">

examples/src/main/python/ml/gaussian_mixture_example.py

@@ -38,7 +38,7 @@
     # loads data
     dataset = spark.read.format("libsvm").load("data/mllib/sample_kmeans_data.txt")
 
-    gmm = GaussianMixture().setK(2).setSeed(10)
+    gmm = GaussianMixture().setK(2)
     model = gmm.fit(dataset)
 
     print("Gaussians: ")