Github user harsha2010 commented on a diff in the pull request:
https://github.com/apache/spark/pull/6996#discussion_r33283398
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -91,74 +60,44 @@ class CrossValidator(override val uid: String) extends
Estimator[CrossValidatorM
private val f2jBLAS = new F2jBLAS
/** @group setParam */
- def setEstimator(value: Estimator[_]): this.type = set(estimator, value)
-
- /** @group setParam */
- def setEstimatorParamMaps(value: Array[ParamMap]): this.type =
set(estimatorParamMaps, value)
-
- /** @group setParam */
- def setEvaluator(value: Evaluator): this.type = set(evaluator, value)
-
- /** @group setParam */
def setNumFolds(value: Int): this.type = set(numFolds, value)
- override def fit(dataset: DataFrame): CrossValidatorModel = {
+ override protected[ml] def validationLogic(
+ dataset: DataFrame,
+ est: Estimator[_],
+ eval: Evaluator,
+ epm: Array[ParamMap],
+ numModels: Int): Array[Double] = {
+
val schema = dataset.schema
transformSchema(schema, logging = true)
val sqlCtx = dataset.sqlContext
- val est = $(estimator)
- val eval = $(evaluator)
- val epm = $(estimatorParamMaps)
- val numModels = epm.length
+
val metrics = new Array[Double](epm.length)
val splits = MLUtils.kFold(dataset.rdd, $(numFolds), 0)
+
splits.zipWithIndex.foreach { case ((training, validation),
splitIndex) =>
val trainingDataset = sqlCtx.createDataFrame(training,
schema).cache()
val validationDataset = sqlCtx.createDataFrame(validation,
schema).cache()
- // multi-model training
logDebug(s"Train split $splitIndex with multiple sets of
parameters.")
- val models = est.fit(trainingDataset,
epm).asInstanceOf[Seq[Model[_]]]
- trainingDataset.unpersist()
+ val newMetrics = measureModels(trainingDataset, validationDataset,
est, eval, epm, numModels)
--- End diff --
perhaps a more descriptive name than newMetrics might be metricsPerSplit?
or something better.
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