[MINOR][ML] Use coefficients replace weights

Use ```coefficients``` replace ```weights```, I wish they are the last two.
mengxr

Author: Yanbo Liang <[email protected]>

Closes #10065 from yanboliang/coefficients.

(cherry picked from commit d576e76)
Signed-off-by: Xiangrui Meng <[email protected]>

Author: yanboliang

python/pyspark/ml/classification.py

@@ -49,7 +49,7 @@ class LogisticRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredicti
     ...     Row(label=0.0, weight=2.0, features=Vectors.sparse(1, [], []))]).toDF()
     >>> lr = LogisticRegression(maxIter=5, regParam=0.01, weightCol="weight")
     >>> model = lr.fit(df)
-    >>> model.weights
+    >>> model.coefficients
     DenseVector([5.5...])
     >>> model.intercept
     -2.68...

python/pyspark/ml/regression.py

@@ -40,7 +40,7 @@ class LinearRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPrediction
     Linear regression.
 
     The learning objective is to minimize the squared error, with regularization.
-    The specific squared error loss function used is: L = 1/2n ||A weights - y||^2^
+    The specific squared error loss function used is: L = 1/2n ||A coefficients - y||^2^
 
     This support multiple types of regularization:
      - none (a.k.a. ordinary least squares)