diff options
Diffstat (limited to 'mllib')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala | 3 | ||||
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala | 17 |
2 files changed, 20 insertions, 0 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala index 8ffbcf0d8b..b0a6af171c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala @@ -53,6 +53,9 @@ private[shared] object SharedParamsCodeGen { ParamDesc[Int]("checkpointInterval", "checkpoint interval (>= 1)", isValid = "ParamValidators.gtEq(1)"), ParamDesc[Boolean]("fitIntercept", "whether to fit an intercept term", Some("true")), + ParamDesc[Boolean]("standardization", "whether to standardize the training features" + + " prior to fitting the model sequence. Note that the coefficients of models are" + + " always returned on the original scale.", Some("true")), ParamDesc[Long]("seed", "random seed", Some("this.getClass.getName.hashCode.toLong")), ParamDesc[Double]("elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]." + " For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala index a0c8ccdac9..bbe08939b6 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala @@ -234,6 +234,23 @@ private[ml] trait HasFitIntercept extends Params { } /** + * (private[ml]) Trait for shared param standardization (default: true). + */ +private[ml] trait HasStandardization extends Params { + + /** + * Param for whether to standardize the training features prior to fitting the model sequence. Note that the coefficients of models are always returned on the original scale.. + * @group param + */ + final val standardization: BooleanParam = new BooleanParam(this, "standardization", "whether to standardize the training features prior to fitting the model sequence. Note that the coefficients of models are always returned on the original scale.") + + setDefault(standardization, true) + + /** @group getParam */ + final def getStandardization: Boolean = $(standardization) +} + +/** * (private[ml]) Trait for shared param seed (default: this.getClass.getName.hashCode.toLong). */ private[ml] trait HasSeed extends Params { |