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class Model extends AnyRef

Model

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Known Subclasses
DateTimeModel, FrozenModel, PrimeModel
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Instance Constructors

  1. new Model(featurelistId: String, processes: Array[String], featurelistName: String, projectId: String, samplePct: Option[Double], trainingDuration: Option[String], trainingRowCount: Option[Int], trainingStartDate: Option[String], trainingEndDate: Option[String], modelCategory: String, isFrozen: Boolean = false, metrics: Map[String, Metric], modelType: String, blueprintId: String, monotonicIncreasingFeaturelistId: Option[String] = None, monotonicDecreasingFeaturelistId: Option[String] = None, supportsMonotonicConstraints: Option[Boolean] = None, id: String, isStarred: Boolean = false, predictionThreshold: Option[Double], predictionThresholdReadOnly: Option[Boolean])

    featurelistId

    the ID of the featurelist used by the model

    processes

    a json list of processes used by the model

    featurelistName

    the name of the featurelist used by the model

    projectId

    the ID of the project to which the model belongs

    samplePct

    the percentage of the dataset used in training the model

    trainingDuration

    the duration spanned by the dates in the partition column for the data used to train the model

    trainingRowCount

    the number of rows used to train the model

    trainingStartDate

    the start date of the dates in the partition column for the data used to train the model

    trainingEndDate

    the end date of the dates in the partition column for the data used to train the model

    modelCategory

    indicateswhatkindofmodelitis -willbeprimeforDataRobotPrime models, blend for blender models, scaleout for scaleout models, and model for all other models

    isFrozen

    boolean, indicating whether the model is frozen, i.e. uses tuning parameters from a parent model

    metrics

    the performance of the model according to various metrics, see below

    modelType

    identifies the model, e.g. Nystroem Kernel SVM Regressor

    blueprintId

    the blueprint used to construct the model - note this is not an ObjectId

    monotonicIncreasingFeaturelistId

    (new in v2.11) null or str, the ID of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If null, no such constraints are enforced.

    monotonicDecreasingFeaturelistId

    (new in v2.11) null or str, the ID of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If null, no such constraints are enforced.

    supportsMonotonicConstraints

    (new in v2.11) boolean, whether this model supports enforcing montonic constraints

    id

    Model ID

    isStarred

    (bool) (New in version v2.13) whether the model has been starred

    predictionThreshold

    (float) (New in version v2.13) threshold used for binary classification in predictions.

    predictionThresholdReadOnly

    (boolean) (New in version v2.13) indicates whether modification of a predictions threshold is forbidden. Threshold modification is forbidden once a model has had a deployment created or predictions made via the dedicated prediction API.

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
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  3. final def ==(arg0: Any): Boolean
    Definition Classes
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  4. def advancedTuning(description: String)(implicit client: DataRobotClient): AdvancedTuningSession
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. val blueprintId: String
  7. def clone(): AnyRef
    Attributes
    protected[lang]
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    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. val featurelistId: String
  11. val featurelistName: String
  12. def getCapabilities()(implicit client: DataRobotClient): (Map[String, Boolean], Map[String, String])
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  14. def getCrossValidationScores()(implicit client: DataRobotClient): Map[String, Map[String, Map[String, Double]]]
  15. def getFeatureEffects(source: String = "validation", backtestIndex: Option[String] = None)(implicit client: DataRobotClient): FeatureEffects
  16. def getFeatureEffectsMetaData()(implicit client: DataRobotClient): String
  17. def getFeatureFit(source: String = "validation", backtestIndex: Option[String] = None)(implicit client: DataRobotClient): FeatureFits
  18. def getFeatureFitMetaData()(implicit client: DataRobotClient): String
  19. def getFeatureImpact()(implicit client: DataRobotClient): FeatureImpacts
  20. def getHyperParameters()(implicit client: DataRobotClient): Map[String, List[Map[String, Any]]]
  21. def getLiftChart(source: enums.Source.Value)(implicit client: DataRobotClient): LiftChart
  22. def getLiftCharts()(implicit client: DataRobotClient): Map[String, List[LiftChart]]
  23. def getMissingValueReport()(implicit client: DataRobotClient): List[Map[_ <: String, Any]]
  24. def getModelBlueprintChart()(implicit client: DataRobotClient): Graph[BlueprintNode, LDiEdge]
  25. def getModelCoefficients()(implicit client: DataRobotClient): ModelCoefficients
  26. def getResiduals()(implicit client: DataRobotClient): Map[String, Map[String, ResidualData]]
  27. def getRocCurve(source: enums.Source.Value)(implicit client: DataRobotClient): RocCurve
  28. def getRocCurves()(implicit client: DataRobotClient): Map[String, List[RocCurve]]
  29. def getScoringCode(destination: Option[String] = None, sourceCode: Boolean = false)(implicit client: DataRobotClient): Unit
  30. def getWordCloud()(implicit client: DataRobotClient): WordCloud
  31. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  32. val id: String
  33. val isFrozen: Boolean
  34. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  35. var isStarred: Boolean
  36. val metrics: Map[String, Metric]
  37. val modelCategory: String
  38. val modelType: String
  39. val monotonicDecreasingFeaturelistId: Option[String]
  40. val monotonicIncreasingFeaturelistId: Option[String]
  41. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  42. final def notify(): Unit
    Definition Classes
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    @native() @HotSpotIntrinsicCandidate()
  43. final def notifyAll(): Unit
    Definition Classes
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    @native() @HotSpotIntrinsicCandidate()
  44. var predictionThreshold: Option[Double]
  45. var predictionThresholdReadOnly: Option[Boolean]
  46. val processes: Array[String]
  47. val projectId: String
  48. def requestAndGetFeatureEffects(source: String = "validation", backtestIndex: Option[String] = None)(implicit client: DataRobotClient): FeatureEffects
  49. def requestAndGetFeatureFit(source: String = "validation", backtestIndex: Option[String] = None)(implicit client: DataRobotClient): FeatureFits
  50. def requestAndGetFeatureImpact(maxWait: Int = 600000)(implicit client: DataRobotClient): AnyRef
  51. def requestFeatureEffects(backtestIndex: Option[String] = None)(implicit client: DataRobotClient): Job
  52. def requestFeatureFit(backtestIndex: Option[String] = None)(implicit client: DataRobotClient): Job
  53. def requestFeatureImpact()(implicit client: DataRobotClient): Job
  54. def requestFrozenModel(samplePct: Option[Float] = None, trainingRowCount: Option[Int] = None)(implicit client: DataRobotClient): ModelJob
  55. def requestPredictions(datasetId: String, includePredictionIntervals: Option[Boolean] = None, predictionIntervalSize: Option[Int] = None, forecastPoint: Option[String] = None, predictionsStartDate: Option[String] = None, predictionsEndDate: Option[String] = None)(implicit client: DataRobotClient): PredictJob
  56. def runCrossValidation()(implicit client: DataRobotClient): Job
  57. val samplePct: Option[Double]
  58. def starModel()(implicit client: DataRobotClient): Model
  59. val supportsMonotonicConstraints: Option[Boolean]
  60. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  61. def toString(): String
    Definition Classes
    Model → AnyRef → Any
  62. def toggleStar(starred: Boolean)(implicit client: DataRobotClient): Model
  63. val trainingDuration: Option[String]
  64. val trainingEndDate: Option[String]
  65. val trainingRowCount: Option[Int]
  66. val trainingStartDate: Option[String]
  67. def unstarModel()(implicit client: DataRobotClient): Model
  68. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
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    @throws( ... )
  69. final def wait(arg0: Long): Unit
    Definition Classes
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    @throws( ... ) @native()
  70. final def wait(): Unit
    Definition Classes
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    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
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    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

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