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author | Shivaram Venkataraman <shivaram@eecs.berkeley.edu> | 2013-08-30 00:16:32 -0700 |
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committer | Shivaram Venkataraman <shivaram@eecs.berkeley.edu> | 2013-08-30 00:16:32 -0700 |
commit | adc700582b52c730a4dbf2a45d4cc794be43cfe5 (patch) | |
tree | ccd7afd19ed2e85dc0f91cd620c30bc0e1307b45 /mllib | |
parent | 016787de321519c1e06daaf3e195a7e7e6a9e0b2 (diff) | |
download | spark-adc700582b52c730a4dbf2a45d4cc794be43cfe5.tar.gz spark-adc700582b52c730a4dbf2a45d4cc794be43cfe5.tar.bz2 spark-adc700582b52c730a4dbf2a45d4cc794be43cfe5.zip |
Fix broken build by removing addIntercept
Diffstat (limited to 'mllib')
-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) } /** |