ai.h2o.sparkling.ml.params.H2OAutoMLInputParams.scala Maven / Gradle / Ivy

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * 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
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package ai.h2o.sparkling.ml.params

import ai.h2o.automl.AutoMLBuildSpec.AutoMLInput
import ai.h2o.sparkling.H2OFrame
import ai.h2o.sparkling.ml.utils.H2OAutoMLSortMetric

trait H2OAutoMLInputParams
  extends H2OAlgoParamsBase
  with HasIgnoredCols
  with HasLeaderboardDataFrame
  with HasBlendingDataFrame {


  //
  // Parameter definitions
  //
  protected val labelCol = stringParam(
    name = "labelCol",
    doc = """Response column.""")

  protected val foldCol = nullableStringParam(
    name = "foldCol",
    doc = """Fold column (contains fold IDs) in the training frame. These assignments are used to create the folds for cross-validation of the models.""")

  protected val weightCol = nullableStringParam(
    name = "weightCol",
    doc = """Weights column in the training frame, which specifies the row weights used in model training.""")

  protected val sortMetric = stringParam(
    name = "sortMetric",
    doc = """Metric used to sort leaderboard. Possible values are ``"AUTO"``, ``"deviance"``, ``"logloss"``, ``"MSE"``, ``"RMSE"``, ``"MAE"``, ``"RMSLE"``, ``"AUC"``, ``"mean_per_class_error"``.""")

  //
  // Default values
  //
  setDefault(
    labelCol -> "label",
    foldCol -> null,
    weightCol -> null,
    sortMetric -> H2OAutoMLSortMetric.AUTO.name())

  //
  // Getters
  //
  def getLabelCol(): String = $(labelCol)

  def getFoldCol(): String = $(foldCol)

  def getWeightCol(): String = $(weightCol)

  def getSortMetric(): String = $(sortMetric)

  //
  // Setters
  //
  def setLabelCol(value: String): this.type = {
    set(labelCol, value)
  }
           
  def setFoldCol(value: String): this.type = {
    set(foldCol, value)
  }
           
  def setWeightCol(value: String): this.type = {
    set(weightCol, value)
  }
           
  def setSortMetric(value: String): this.type = {
    val validated = EnumParamValidator.getValidatedEnumValue[H2OAutoMLSortMetric](value)
    set(sortMetric, validated)
  }
           

  override private[sparkling] def getH2OAlgorithmParams(trainingFrame: H2OFrame): Map[String, Any] = {
    super.getH2OAlgorithmParams(trainingFrame) ++ getH2OAutoMLInputParams(trainingFrame)
  }

  private[sparkling] def getH2OAutoMLInputParams(trainingFrame: H2OFrame): Map[String, Any] = {
      Map(
        "response_column" -> getLabelCol(),
        "fold_column" -> getFoldCol(),
        "weights_column" -> getWeightCol(),
        "sort_metric" -> getSortMetric()) +++
      getIgnoredColsParam(trainingFrame) +++
      getLeaderboardDataFrameParam(trainingFrame) +++
      getBlendingDataFrameParam(trainingFrame)
  }

  override private[sparkling] def getSWtoH2OParamNameMap(): Map[String, String] = {
    super.getSWtoH2OParamNameMap() ++
      Map(
        "labelCol" -> "response_column",
        "foldCol" -> "fold_column",
        "weightCol" -> "weights_column",
        "sortMetric" -> "sort_metric")
  }
      
}