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mimir.ml.spark

SparkML

Related Docs: object SparkML | package spark

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abstract class SparkML extends AnyRef

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Instance Constructors

  1. new SparkML()

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Type Members

  1. type DataFrameTransformer = (DataFrame) ⇒ DataFrame

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  2. type ValuePreparer = (PrimitiveValue, Type) ⇒ Any

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Abstract Value Members

  1. abstract def extractPredictions(model: PipelineModel, predictions: DataFrame, maxPredictions: Int = 5): Seq[(String, (String, Double))]

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  2. abstract def extractPredictionsForRow(model: PipelineModel, predictions: DataFrame, rowid: String, maxPredictions: Int = 5): Seq[(String, Double)]

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  3. abstract def getSparkType(t: Type): DataType

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  4. abstract def prepareValueApply(value: PrimitiveValue, t: Type): Any

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  5. abstract def prepareValueTrain(value: PrimitiveValue, t: Type): Any

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Concrete Value Members

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

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def applyModel(model: PipelineModel, cols: Seq[(String, Type)], testData: List[Seq[PrimitiveValue]], valuePreparer: ValuePreparer = prepareValueApply, sparkTyper: (Type) ⇒ DataType = getSparkType, dfTransformer: Option[DataFrameTransformer] = None): DataFrame

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  5. def applyModelDB(model: PipelineModel, query: Operator, db: Database, valuePreparer: ValuePreparer = prepareValueApply, sparkTyper: (Type) ⇒ DataType = getSparkType, dfTransformer: Option[DataFrameTransformer] = None): DataFrame

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def getSparkSession(): SparkContext

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  13. def getSparkSqlContext(): SQLContext

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def nullValueReplacement(df: DataFrame): DataFrame

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  20. def prepareData(query: Operator, db: Database, valuePreparer: ValuePreparer = prepareValueTrain, sparkTyper: (Type) ⇒ DataType = getSparkType): DataFrame

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

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  22. def toString(): String

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  23. final def wait(): Unit

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

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  25. final def wait(arg0: Long): Unit

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