setting

Type Members

1. trait AbstractIOSpec extends AnyRef

   

2. case class ClassificationLearningSetting(featuresNormalizationType: Option[VectorScalerType.Value] = None, featuresSelectionNum: Option[Int] = None, pcaDims: Option[Int] = None, trainingTestSplitRatio: Option[Double] = None, samplingRatios: Seq[(String, Double)] = Nil, repetitions: Option[Int] = None, crossValidationFolds: Option[Int] = None, crossValidationEvalMetric: Option[classification.ClassificationEvalMetric.Value] = None, binCurvesNumBins: Option[Int] = None, collectOutputs: Boolean = false) extends LearningSetting[classification.ClassificationEvalMetric.Value] with Product with Serializable

   

3. case class ClassificationRunSpec(ioSpec: IOSpec, mlModelId: BSONObjectID, learningSetting: ClassificationLearningSetting) extends RunSpec with Product with Serializable

   

4. case class IOSpec(inputFieldNames: Seq[String], outputFieldName: String, filterId: Option[BSONObjectID] = None, replicationFilterId: Option[BSONObjectID] = None) extends AbstractIOSpec with Product with Serializable

   

5. trait LearningSetting[T] extends AnyRef

   

6. case class RegressionLearningSetting(featuresNormalizationType: Option[VectorScalerType.Value] = None, outputNormalizationType: Option[VectorScalerType.Value] = None, pcaDims: Option[Int] = None, trainingTestSplitRatio: Option[Double] = None, repetitions: Option[Int] = None, crossValidationFolds: Option[Int] = None, crossValidationEvalMetric: Option[regression.RegressionEvalMetric.Value] = None, collectOutputs: Boolean = false) extends LearningSetting[regression.RegressionEvalMetric.Value] with Product with Serializable

   

7. case class RegressionRunSpec(ioSpec: IOSpec, mlModelId: BSONObjectID, learningSetting: RegressionLearningSetting) extends RunSpec with Product with Serializable

   

8. trait RunSpec extends AnyRef

   

9. case class TemporalClassificationLearningSetting(core: ClassificationLearningSetting = ClassificationLearningSetting(), predictAhead: Int = 1, slidingWindowSize: ValueOrSeq[Int] = Left(None), reservoirSetting: Option[ReservoirSpec] = None, minCrossValidationTrainingSizeRatio: Option[Double] = None, trainingTestSplitOrderValue: Option[Double] = None) extends TemporalLearningSetting with Product with Serializable

   

10. case class TemporalClassificationRunSpec(ioSpec: TemporalGroupIOSpec, mlModelId: BSONObjectID, learningSetting: TemporalClassificationLearningSetting) extends RunSpec with Product with Serializable

    

11. case class TemporalGroupIOSpec(inputFieldNames: Seq[String], outputFieldName: String, groupIdFieldName: String, orderFieldName: String, orderedStringValues: Seq[String] = Nil, filterId: Option[BSONObjectID] = None, replicationFilterId: Option[BSONObjectID] = None) extends AbstractIOSpec with Product with Serializable

    

12. trait TemporalLearningSetting extends AnyRef

    

13. case class TemporalRegressionLearningSetting(core: RegressionLearningSetting = RegressionLearningSetting(), predictAhead: Int = 1, slidingWindowSize: ValueOrSeq[Int] = Left(None), reservoirSetting: Option[ReservoirSpec] = None, minCrossValidationTrainingSizeRatio: Option[Double] = None, trainingTestSplitOrderValue: Option[Double] = None) extends TemporalLearningSetting with Product with Serializable

    

14. case class TemporalRegressionRunSpec(ioSpec: TemporalGroupIOSpec, mlModelId: BSONObjectID, learningSetting: TemporalRegressionLearningSetting) extends RunSpec with Product with Serializable