diff --git a/python/pyspark/mllib/classification.py b/python/pyspark/mllib/classification.py
index 0a508f112df33..bd43e91afd280 100644
--- a/python/pyspark/mllib/classification.py
+++ b/python/pyspark/mllib/classification.py
@@ -97,7 +97,7 @@ class LogisticRegressionModel(LinearClassificationModel):
     intercept : float
         Intercept computed for this model. (Only used in Binary Logistic
         Regression. In Multinomial Logistic Regression, the intercepts will
-        not bea single value, so the intercepts will be part of the
+        not be a single value, so the intercepts will be part of the
         weights.)
     numFeatures : int
         The dimension of the features.
@@ -292,7 +292,7 @@ def train(cls, data, iterations=100, step=1.0, miniBatchFraction=1.0,
         step : float, optional
             The step parameter used in SGD.
             (default: 1.0)
-        miniBatchFraction: float, optional
+        miniBatchFraction : float, optional
             Fraction of data to be used for each SGD iteration.
             (default: 1.0)
         initialWeights : :py:class:`pyspark.mllib.linalg.Vector` or convertible, optional
@@ -552,7 +552,7 @@ def train(cls, data, iterations=100, step=1.0, regParam=0.01,
         regParam : float, optional
             The regularizer parameter.
             (default: 0.01)
-        miniBatchFraction: float, optional
+        miniBatchFraction : float, optional
             Fraction of data to be used for each SGD iteration.
             (default: 1.0)
         initialWeights : :py:class:`pyspark.mllib.linalg.Vector` or convertible, optional