[SPARK-2495][MLLIB] remove private[mllib] from linear models' constructors

This is part of SPARK-2495 to allow users construct linear models manually.

Author: Xiangrui Meng <meng@databricks.com>

Closes #1492 from mengxr/public-constructor and squashes the following commits:

a48b766 [Xiangrui Meng] remove private[mllib] from linear models' constructors

mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala

@@ -30,7 +30,7 @@ import org.apache.spark.rdd.RDD
  * @param weights Weights computed for every feature.
  * @param intercept Intercept computed for this model.
  */
-class LogisticRegressionModel private[mllib] (
+class LogisticRegressionModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable {

mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala

@@ -30,7 +30,7 @@ import org.apache.spark.rdd.RDD
  * @param weights Weights computed for every feature.
  * @param intercept Intercept computed for this model.
  */
-class SVMModel private[mllib] (
+class SVMModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable {

mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala

@@ -28,7 +28,7 @@ import org.apache.spark.rdd.RDD
  * @param weights Weights computed for every feature.
  * @param intercept Intercept computed for this model.
  */
-class LassoModel private[mllib] (
+class LassoModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept)

mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala

@@ -27,7 +27,7 @@ import org.apache.spark.mllib.optimization._
  * @param weights Weights computed for every feature.
  * @param intercept Intercept computed for this model.
  */
-class LinearRegressionModel private[mllib] (
+class LinearRegressionModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with RegressionModel with Serializable {

mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala

@@ -28,7 +28,7 @@ import org.apache.spark.mllib.linalg.Vector
  * @param weights Weights computed for every feature.
  * @param intercept Intercept computed for this model.
  */
-class RidgeRegressionModel private[mllib] (
+class RidgeRegressionModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept)