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[SPARK-2495][MLLIB] remove private[mllib] from linear models' constru…
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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
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mengxr authored and rxin committed Jul 20, 2014
1 parent fa51b0f commit 1b10b81
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Showing 5 changed files with 5 additions and 5 deletions.
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Expand Up @@ -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 {
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Expand Up @@ -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 {
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Expand Up @@ -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)
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Expand Up @@ -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 {
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Expand Up @@ -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)
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