diff options
-rw-r--r-- | mllib/src/main/scala/spark/mllib/regression/LinearRegression.scala | 9 | ||||
-rw-r--r-- | mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala | 10 |
2 files changed, 8 insertions, 11 deletions
diff --git a/mllib/src/main/scala/spark/mllib/regression/LinearRegression.scala b/mllib/src/main/scala/spark/mllib/regression/LinearRegression.scala index 5b3743f2fa..885ff5a30d 100644 --- a/mllib/src/main/scala/spark/mllib/regression/LinearRegression.scala +++ b/mllib/src/main/scala/spark/mllib/regression/LinearRegression.scala @@ -47,8 +47,7 @@ class LinearRegressionModel( class LinearRegressionWithSGD private ( var stepSize: Double, var numIterations: Int, - var miniBatchFraction: Double, - var addIntercept: Boolean) + var miniBatchFraction: Double) extends GeneralizedLinearAlgorithm[LinearRegressionModel] with Serializable { @@ -61,7 +60,7 @@ class LinearRegressionWithSGD private ( /** * Construct a LinearRegression object with default parameters */ - def this() = this(1.0, 100, 1.0, true) + def this() = this(1.0, 100, 1.0) def createModel(weights: Array[Double], intercept: Double) = { new LinearRegressionModel(weights, intercept) @@ -94,7 +93,7 @@ object LinearRegressionWithSGD { initialWeights: Array[Double]) : LinearRegressionModel = { - new LinearRegressionWithSGD(stepSize, numIterations, miniBatchFraction, true).run(input, + new LinearRegressionWithSGD(stepSize, numIterations, miniBatchFraction).run(input, initialWeights) } @@ -115,7 +114,7 @@ object LinearRegressionWithSGD { miniBatchFraction: Double) : LinearRegressionModel = { - new LinearRegressionWithSGD(stepSize, numIterations, miniBatchFraction, true).run(input) + new LinearRegressionWithSGD(stepSize, numIterations, miniBatchFraction).run(input) } /** diff --git a/mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala b/mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala index ccf7364806..cb1303dd99 100644 --- a/mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala +++ b/mllib/src/main/scala/spark/mllib/regression/RidgeRegression.scala @@ -48,8 +48,7 @@ class RidgeRegressionWithSGD private ( var stepSize: Double, var numIterations: Int, var regParam: Double, - var miniBatchFraction: Double, - var addIntercept: Boolean) + var miniBatchFraction: Double) extends GeneralizedLinearAlgorithm[RidgeRegressionModel] with Serializable { @@ -71,7 +70,7 @@ class RidgeRegressionWithSGD private ( /** * Construct a RidgeRegression object with default parameters */ - def this() = this(1.0, 100, 1.0, 1.0, true) + def this() = this(1.0, 100, 1.0, 1.0) def createModel(weights: Array[Double], intercept: Double) = { val weightsMat = new DoubleMatrix(weights.length + 1, 1, (Array(intercept) ++ weights):_*) @@ -134,7 +133,7 @@ object RidgeRegressionWithSGD { initialWeights: Array[Double]) : RidgeRegressionModel = { - new RidgeRegressionWithSGD(stepSize, numIterations, regParam, miniBatchFraction, true).run( + new RidgeRegressionWithSGD(stepSize, numIterations, regParam, miniBatchFraction).run( input, initialWeights) } @@ -157,8 +156,7 @@ object RidgeRegressionWithSGD { miniBatchFraction: Double) : RidgeRegressionModel = { - new RidgeRegressionWithSGD(stepSize, numIterations, regParam, miniBatchFraction, true).run( - input) + new RidgeRegressionWithSGD(stepSize, numIterations, regParam, miniBatchFraction).run(input) } /** |