XGBoost

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. final def asInstanceOf[T0]: T0

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5. def clone(): AnyRef

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6. def crossValidation(data: DMatrix, params: Map[String, Any], round: Int, nfold: Int = 5, metrics: Array[String] = null, obj: ObjectiveTrait = null, eval: EvalTrait = null): Array[String]

   Cross-validation with given parameters.

   Cross-validation with given parameters.

   data

   Data to be trained.

   params

   Booster params.

   round

   Number of boosting iterations.

   nfold

   Number of folds in CV.

   metrics

   Evaluation metrics to be watched in CV.

   obj

   customized objective

   eval

   customized evaluation

   returns

   evaluation history

   Annotations

   @throws( classOf[XGBoostError] )

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

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8. def equals(arg0: Any): Boolean

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9. def finalize(): Unit

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

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11. def hashCode(): Int

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12. final def isInstanceOf[T0]: Boolean

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13. def loadModel(in: InputStream): Booster

    Load a new Booster model from a file opened as input stream.

    Load a new Booster model from a file opened as input stream. The assumption is the input stream only contains one XGBoost Model. This can be used to load existing booster models saved by other XGBoost bindings.

    in

    The input stream of the file.

    returns

    The create booster

    Annotations

    @throws( classOf[XGBoostError] )

14. def loadModel(modelPath: String): Booster

    load model from modelPath

    load model from modelPath

    modelPath

    booster modelPath

    Annotations

    @throws( classOf[XGBoostError] )

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

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16. final def notify(): Unit

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17. final def notifyAll(): Unit

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

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19. def toString(): String

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20. def train(dtrain: DMatrix, params: Map[String, Any], round: Int, watches: Map[String, DMatrix] = Map[String, DMatrix](), obj: ObjectiveTrait = null, eval: EvalTrait = null): Booster

    Train a booster given parameters.

    Train a booster given parameters.

    dtrain

    Data to be trained.

    params

    Parameters.

    round

    Number of boosting iterations.

    watches

    a group of items to be evaluated during training, this allows user to watch performance on the validation set.

    obj

    customized objective

    eval

    customized evaluation

    returns

    The trained booster.

    Annotations

    @throws( classOf[XGBoostError] )

21. final def wait(): Unit

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

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

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