Add a param to skip invalid entries.

Author: holdenk

mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala

@@ -53,6 +53,7 @@ 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]("skipInvalid", "whether to skip invalid entries"),
       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")),

mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala

@@ -233,6 +233,21 @@ private[ml] trait HasFitIntercept extends Params {
   final def getFitIntercept: Boolean = $(fitIntercept)
 }
 
+/**
+ * (private[ml]) Trait for shared param skipInvalid.
+ */
+private[ml] trait HasSkipInvalid extends Params {
+
+  /**
+   * Param for whether to skip invalid entries.
+   * @group param
+   */
+  final val skipInvalid: BooleanParam = new BooleanParam(this, "skipInvalid", "whether to skip invalid entries")
+
+  /** @group getParam */
+  final def getSkipInvalid: Boolean = $(skipInvalid)
+}
+
 /**
  * (private[ml]) Trait for shared param standardization (default: true).
  */