Class

com.microsoft.ml.spark

LightGBMBooster

Related Doc: package spark

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class LightGBMBooster extends Serializable

Represents a LightGBM Booster learner

Linear Supertypes
Serializable, Serializable, AnyRef, Any
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Visibility
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Instance Constructors

  1. new LightGBMBooster(model: String)

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    model

    The string serialized representation of the learner

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. var boosterPtr: SWIGTYPE_p_void

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    Transient variable containing local machine's pointer to native booster

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
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    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef

  8. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  9. def finalize(): Unit

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    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
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  11. def getFeatureImportances(importanceType: String): Array[Double]

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    Calls into LightGBM to retrieve the feature importances.

    Calls into LightGBM to retrieve the feature importances.

    importanceType

    Can be "split" or "gain"

    returns

    The feature importance values as an array.

  12. def getModel(): SWIGTYPE_p_void

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    Attributes
    protected

  13. def hashCode(): Int

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    Definition Classes
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  14. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  15. val model: String

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    The string serialized representation of the learner

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

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    Definition Classes
    AnyRef

  17. final def notify(): Unit

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    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  19. def predictForCSR(sparseVector: SparseVector, kind: Int): Double

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    Attributes
    protected

  20. def predictForMat(row: Array[Double], kind: Int): Double

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    Attributes
    protected

  21. def saveNativeModel(session: SparkSession, filename: String): Unit

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  22. def score(features: Vector, raw: Boolean): Double

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

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    Definition Classes
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  24. def toString(): String

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    Definition Classes
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  25. final def wait(): Unit

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    @throws( ... )

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

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    Definition Classes
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    @throws( ... )

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

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    Definition Classes
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    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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