Class

io.github.timsetsfire.datarobot

Partition

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class Partition extends AnyRef

Partitioning for a given project that will be returned as part of a response from API

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Instance Constructors

  1. new Partition(cvMethod: Option[enums.CVMethod.Value] = None, validationType: Option[enums.ValidationType.Value] = None, datetimeCol: Option[String] = None, datetimePartitionColumn: Option[String] = None, validationPct: Option[Double] = None, reps: Option[Int] = None, cvHoldoutLevel: Option[String] = None, holdoutLevel: Option[String] = None, userPartitionCol: Option[String] = None, trainingLevel: Option[String] = None, partitionKeyCols: Option[String] = None, holdoutPct: Option[Double] = None, validationLevel: Option[String] = None, useTimeSeries: Option[Boolean] = None)

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    create a new Partition object

    create a new Partition object

    cvMethod

    the partitioning method used, will be either “random”, “stratified”, “date- time”, “user”, “group”, or “date”. Note that “date” partitioning is an old partitioning method no longer supported for new projects, as of API version v2.0.

    validationType

    – either CV for cross-validation or TVH for train-validation-holdout split

    datetimeCol

    if a date partition column was used, the name of the column Note that datetimeCol applies to an old partitioning method no longer supported for new projects, as of API version v2.0.

    validationPct

    if train-validation-holdoutsplitwasused,thepercentageofthedataset used for the validation set

    reps

    if cross validation was used, the number of folds to use

    cvHoldoutLevel

    if a user partition column was used with cross validation, the value

    holdoutLevel

    if a user partition column was used with train-validation-holdout split, the value assigned to the holdout set

    userPartitionCol

    – if a user partition column was used, the name of the column

    trainingLevel

    – if a user partition column was used with train-validation-holdoutsplit, the value assigned to the training set

    partitionKeyCols

    – if group partitioning was used, the name of the column.

    holdoutPct

    – the percentage of the dataset reserved for the holdout set

    validationLevel

    – if a user partition column was used with train-validation-holdout split, the value assigned to the validation set

    useTimeSeries

    – (New in version v2.9) A boolean value indicating whether a time series project was created as opposed to a regular project using datetime partitioning.

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. val cvHoldoutLevel: Option[String]

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    if a user partition column was used with cross validation, the value

  7. val cvMethod: Option[enums.CVMethod.Value]

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    the partitioning method used, will be either “random”, “stratified”, “date- time”, “user”, “group”, or “date”.

    the partitioning method used, will be either “random”, “stratified”, “date- time”, “user”, “group”, or “date”. Note that “date” partitioning is an old partitioning method no longer supported for new projects, as of API version v2.0.

  8. val datetimeCol: Option[String]

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    if a date partition column was used, the name of the column Note that datetimeCol applies to an old partitioning method no longer supported for new projects, as of API version v2.0.

  9. val datetimePartitionColumn: Option[String]

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  10. final def eq(arg0: AnyRef): Boolean

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  11. def equals(arg0: Any): Boolean

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. val holdoutLevel: Option[String]

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    if a user partition column was used with train-validation-holdout split, the value assigned to the holdout set

  15. val holdoutPct: Option[Double]

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    – the percentage of the dataset reserved for the holdout set

  16. final def isInstanceOf[T0]: Boolean

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  17. final def ne(arg0: AnyRef): Boolean

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. val partitionKeyCols: Option[String]

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    – if group partitioning was used, the name of the column.

  21. val reps: Option[Int]

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    if cross validation was used, the number of folds to use

  22. final def synchronized[T0](arg0: ⇒ T0): T0

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  23. def toString(): String

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  24. val trainingLevel: Option[String]

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    – if a user partition column was used with train-validation-holdoutsplit, the value assigned to the training set

  25. val useTimeSeries: Option[Boolean]

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    – (New in version v2.9) A boolean value indicating whether a time series project was created as opposed to a regular project using datetime partitioning.

  26. val userPartitionCol: Option[String]

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    – if a user partition column was used, the name of the column

  27. val validationLevel: Option[String]

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    – if a user partition column was used with train-validation-holdout split, the value assigned to the validation set

  28. val validationPct: Option[Double]

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    if train-validation-holdoutsplitwasused,thepercentageofthedataset used for the validation set

  29. val validationType: Option[enums.ValidationType.Value]

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    – either CV for cross-validation or TVH for train-validation-holdout split

  30. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  31. final def wait(arg0: Long): Unit

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  32. final def wait(): Unit

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Deprecated Value Members

  1. def finalize(): Unit

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    Deprecated

    (Since version ) see corresponding Javadoc for more information.

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