[MINOR] [MLLIB] rename some functions of PythonMLLibAPI

Keep the same naming conventions for PythonMLLibAPI.
Only the following three functions is different from others
```scala
trainNaiveBayes
trainGaussianMixture
trainWord2Vec
```
So change them to
```scala
trainNaiveBayesModel
trainGaussianMixtureModel
trainWord2VecModel
```
It does not affect any users and public APIs, only to make better understand for developer and code hacker.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #7011 from yanboliang/py-mllib-api-rename and squashes the following commits:

771ffec [Yanbo Liang] rename some functions of PythonMLLibAPI

3 files changed, 5 insertions, 5 deletions

diff --git a/python/pyspark/mllib/classification.py b/python/pyspark/mllib/classification.py
index 2698f10d06..735d45ba03 100644
--- a/python/pyspark/mllib/classification.py
+++ b/python/pyspark/mllib/classification.py
@@ -581,7 +581,7 @@ class NaiveBayes(object):
         first = data.first()
         if not isinstance(first, LabeledPoint):
             raise ValueError("`data` should be an RDD of LabeledPoint")
-        labels, pi, theta = callMLlibFunc("trainNaiveBayes", data, lambda_)
+        labels, pi, theta = callMLlibFunc("trainNaiveBayesModel", data, lambda_)
         return NaiveBayesModel(labels.toArray(), pi.toArray(), numpy.array(theta))
 
 
diff --git a/python/pyspark/mllib/clustering.py b/python/pyspark/mllib/clustering.py
index e6ef72942c..8bc0654c76 100644
--- a/python/pyspark/mllib/clustering.py
+++ b/python/pyspark/mllib/clustering.py
@@ -265,9 +265,9 @@ class GaussianMixture(object):
             initialModelWeights = initialModel.weights
             initialModelMu = [initialModel.gaussians[i].mu for i in range(initialModel.k)]
             initialModelSigma = [initialModel.gaussians[i].sigma for i in range(initialModel.k)]
-        weight, mu, sigma = callMLlibFunc("trainGaussianMixture", rdd.map(_convert_to_vector), k,
-                                          convergenceTol, maxIterations, seed, initialModelWeights,
-                                          initialModelMu, initialModelSigma)
+        weight, mu, sigma = callMLlibFunc("trainGaussianMixtureModel", rdd.map(_convert_to_vector),
+                                          k, convergenceTol, maxIterations, seed,
+                                          initialModelWeights, initialModelMu, initialModelSigma)
         mvg_obj = [MultivariateGaussian(mu[i], sigma[i]) for i in range(k)]
         return GaussianMixtureModel(weight, mvg_obj)
 
diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py
index 334f5b86cd..f00bb93b7b 100644
--- a/python/pyspark/mllib/feature.py
+++ b/python/pyspark/mllib/feature.py
@@ -549,7 +549,7 @@ class Word2Vec(object):
         """
         if not isinstance(data, RDD):
             raise TypeError("data should be an RDD of list of string")
-        jmodel = callMLlibFunc("trainWord2Vec", data, int(self.vectorSize),
+        jmodel = callMLlibFunc("trainWord2VecModel", data, int(self.vectorSize),
                                float(self.learningRate), int(self.numPartitions),
                                int(self.numIterations), int(self.seed),
                                int(self.minCount))