ai.h2o.sparkling.ml.params.HasRandomCols.scala Maven / Gradle / Ivy
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* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package ai.h2o.sparkling.ml.params
import ai.h2o.sparkling.H2OFrame
import ai.h2o.sparkling.ml.algos.H2OAlgoCommonUtils
trait HasRandomCols extends H2OAlgoParamsBase with H2OAlgoCommonUtils {
private val randomCols = new NullableStringArrayParam(this, "randomCols", "Names of random columns for HGLM.")
setDefault(randomCols -> null)
def getRandomCols(): Array[String] = $(randomCols)
def setRandomCols(value: Array[String]): this.type = set(randomCols, value)
private[sparkling] def getRandomColsParam(trainingFrame: H2OFrame): Map[String, Any] = {
val randomColumnNames = getRandomCols()
val indices = if (randomColumnNames == null) {
null
} else {
val frameColumns = trainingFrame.columnNames
val indices = randomColumnNames.map(col => frameColumns.indexOf(col))
indices
}
Map("random_columns" -> indices, "ignored_columns" -> randomColumnNames)
}
override private[sparkling] def getSWtoH2OParamNameMap(): Map[String, String] = {
super.getSWtoH2OParamNameMap() ++ Map("randomCols" -> "random_columns")
}
override private[sparkling] def getExcludedCols(): Seq[String] = {
val randomCols = getRandomCols()
if (randomCols == null) {
super.getExcludedCols()
} else {
super.getExcludedCols() ++ randomCols
}
}
}
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