[MLLIB] Add fit intercept term

Added unit tests and changed docs in line with PR comments

mllib/src/main/scala/org/apache/spark/ml/param/sharedParams.scala

@@ -111,7 +111,8 @@ private[ml] trait HasFitIntercept extends Params {
    * param for fitting the intercept term
    * @group param
    */
-  val fitIntercept: BooleanParam = new BooleanParam(this, "fitIntercept", "fits the intercept term or not")
+  val fitIntercept: BooleanParam =
+    new BooleanParam(this, "fitIntercept", "indicates whether to fit an intercept term")
 
   /** @group getParam */
   def getFitIntercept: Boolean = get(fitIntercept)

mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala

@@ -46,6 +46,7 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext {
     assert(lr.getPredictionCol == "prediction")
     assert(lr.getRawPredictionCol == "rawPrediction")
     assert(lr.getProbabilityCol == "probability")
+    assert(lr.getFitIntercept == true)
     val model = lr.fit(dataset)
     model.transform(dataset)
       .select("label", "probability", "prediction", "rawPrediction")
@@ -55,6 +56,14 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext {
     assert(model.getPredictionCol == "prediction")
     assert(model.getRawPredictionCol == "rawPrediction")
     assert(model.getProbabilityCol == "probability")
+    assert(model.intercept != 0.0)
+  }
+
+  test("logistic regression doesn't fit intercept when fitIntercept is off") {
+    val lr = new LogisticRegression
+    lr.setFitIntercept(false)
+    val model = lr.fit(dataset)
+    assert(model.intercept == 0.0)
   }
 
   test("logistic regression with setters") {