Packages

class ComputeModelStatistics extends Transformer with ComputeModelStatisticsParams with BasicLogging

Evaluates the given scored dataset.

Linear Supertypes
BasicLogging, ComputeModelStatisticsParams, HasEvaluationMetric, HasScoredLabelsCol, HasScoresCol, HasLabelCol, DefaultParamsWritable, MLWritable, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ComputeModelStatistics
  2. BasicLogging
  3. ComputeModelStatisticsParams
  4. HasEvaluationMetric
  5. HasScoredLabelsCol
  6. HasScoresCol
  7. HasLabelCol
  8. DefaultParamsWritable
  9. MLWritable
  10. Wrappable
  11. DotnetWrappable
  12. RWrappable
  13. PythonWrappable
  14. BaseWrappable
  15. Transformer
  16. PipelineStage
  17. Logging
  18. Params
  19. Serializable
  20. Serializable
  21. Identifiable
  22. AnyRef
  23. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ComputeModelStatistics()
  2. new ComputeModelStatistics(uid: String)

Value Members

  1. final def clear(param: Param[_]): ComputeModelStatistics.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): Transformer
    Definition Classes
    ComputeModelStatistics → Transformer → PipelineStage → Params
  3. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  4. val evaluationMetric: Param[String]
    Definition Classes
    HasEvaluationMetric
  5. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  6. def explainParams(): String
    Definition Classes
    Params
  7. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  8. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  9. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  10. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getEvaluationMetric: String

    Definition Classes
    HasEvaluationMetric
  12. def getLabelCol: String

    Definition Classes
    HasLabelCol
  13. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  14. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  15. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  16. def getScoredLabelsCol: String

    Definition Classes
    HasScoredLabelsCol
  17. def getScoresCol: String

    Definition Classes
    HasScoresCol
  18. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  19. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  20. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  21. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  22. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  23. def logClass(): Unit
    Definition Classes
    BasicLogging
  24. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  25. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  26. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  27. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  28. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  29. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  30. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  31. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  32. lazy val metricsLogger: MetricsLogger
  33. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  34. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  35. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  36. var rocCurve: DataFrame

    The ROC curve evaluated for a binary classifier.

  37. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  38. val scoredLabelsCol: Param[String]

    The name of the scored labels column

    The name of the scored labels column

    Definition Classes
    HasScoredLabelsCol
  39. val scoresCol: Param[String]

    The name of the scores column

    The name of the scores column

    Definition Classes
    HasScoresCol
  40. final def set[T](param: Param[T], value: T): ComputeModelStatistics.this.type
    Definition Classes
    Params
  41. def setEvaluationMetric(value: String): ComputeModelStatistics.this.type

    Definition Classes
    HasEvaluationMetric
  42. def setLabelCol(value: String): ComputeModelStatistics.this.type

    Definition Classes
    HasLabelCol
  43. def setScoredLabelsCol(value: String): ComputeModelStatistics.this.type

    Definition Classes
    HasScoredLabelsCol
  44. def setScoresCol(value: String): ComputeModelStatistics.this.type

    Definition Classes
    HasScoresCol
  45. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  46. def transform(dataset: Dataset[_]): DataFrame

    Calculates the metrics for the given dataset and model.

    Calculates the metrics for the given dataset and model.

    dataset

    the dataset to calculate the metrics for

    returns

    DataFrame whose columns contain the calculated metrics

    Definition Classes
    ComputeModelStatistics → Transformer
  47. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  48. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  49. def transformSchema(schema: StructType): StructType
    Definition Classes
    ComputeModelStatistics → PipelineStage
  50. val uid: String
    Definition Classes
    ComputeModelStatistics → BasicLogging → Identifiable
  51. val ver: String
    Definition Classes
    BasicLogging
  52. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable