diff options
Diffstat (limited to 'mllib')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala | 20 |
1 files changed, 15 insertions, 5 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala index f585aacd45..69ce7f5070 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala @@ -132,7 +132,8 @@ private[python] class PythonMLLibAPI extends Serializable { regParam: Double, regType: String, intercept: Boolean, - validateData: Boolean): JList[Object] = { + validateData: Boolean, + convergenceTol: Double): JList[Object] = { val lrAlg = new LinearRegressionWithSGD() lrAlg.setIntercept(intercept) .setValidateData(validateData) @@ -141,6 +142,7 @@ private[python] class PythonMLLibAPI extends Serializable { .setRegParam(regParam) .setStepSize(stepSize) .setMiniBatchFraction(miniBatchFraction) + .setConvergenceTol(convergenceTol) lrAlg.optimizer.setUpdater(getUpdaterFromString(regType)) trainRegressionModel( lrAlg, @@ -159,7 +161,8 @@ private[python] class PythonMLLibAPI extends Serializable { miniBatchFraction: Double, initialWeights: Vector, intercept: Boolean, - validateData: Boolean): JList[Object] = { + validateData: Boolean, + convergenceTol: Double): JList[Object] = { val lassoAlg = new LassoWithSGD() lassoAlg.setIntercept(intercept) .setValidateData(validateData) @@ -168,6 +171,7 @@ private[python] class PythonMLLibAPI extends Serializable { .setRegParam(regParam) .setStepSize(stepSize) .setMiniBatchFraction(miniBatchFraction) + .setConvergenceTol(convergenceTol) trainRegressionModel( lassoAlg, data, @@ -185,7 +189,8 @@ private[python] class PythonMLLibAPI extends Serializable { miniBatchFraction: Double, initialWeights: Vector, intercept: Boolean, - validateData: Boolean): JList[Object] = { + validateData: Boolean, + convergenceTol: Double): JList[Object] = { val ridgeAlg = new RidgeRegressionWithSGD() ridgeAlg.setIntercept(intercept) .setValidateData(validateData) @@ -194,6 +199,7 @@ private[python] class PythonMLLibAPI extends Serializable { .setRegParam(regParam) .setStepSize(stepSize) .setMiniBatchFraction(miniBatchFraction) + .setConvergenceTol(convergenceTol) trainRegressionModel( ridgeAlg, data, @@ -212,7 +218,8 @@ private[python] class PythonMLLibAPI extends Serializable { initialWeights: Vector, regType: String, intercept: Boolean, - validateData: Boolean): JList[Object] = { + validateData: Boolean, + convergenceTol: Double): JList[Object] = { val SVMAlg = new SVMWithSGD() SVMAlg.setIntercept(intercept) .setValidateData(validateData) @@ -221,6 +228,7 @@ private[python] class PythonMLLibAPI extends Serializable { .setRegParam(regParam) .setStepSize(stepSize) .setMiniBatchFraction(miniBatchFraction) + .setConvergenceTol(convergenceTol) SVMAlg.optimizer.setUpdater(getUpdaterFromString(regType)) trainRegressionModel( SVMAlg, @@ -240,7 +248,8 @@ private[python] class PythonMLLibAPI extends Serializable { regParam: Double, regType: String, intercept: Boolean, - validateData: Boolean): JList[Object] = { + validateData: Boolean, + convergenceTol: Double): JList[Object] = { val LogRegAlg = new LogisticRegressionWithSGD() LogRegAlg.setIntercept(intercept) .setValidateData(validateData) @@ -249,6 +258,7 @@ private[python] class PythonMLLibAPI extends Serializable { .setRegParam(regParam) .setStepSize(stepSize) .setMiniBatchFraction(miniBatchFraction) + .setConvergenceTol(convergenceTol) LogRegAlg.optimizer.setUpdater(getUpdaterFromString(regType)) trainRegressionModel( LogRegAlg, |