ml.dmlc.xgboost4j.scala

XGBoost

object XGBoost

XGBoost Scala Training function.

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  8. 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

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    @throws( classOf[XGBoostError] )
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  14. 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] )
  15. def loadModel(modelPath: String): Booster

    load model from modelPath

    load model from modelPath

    modelPath

    booster modelPath

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    @throws( classOf[XGBoostError] )
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  21. def train(dtrain: DMatrix, params: Map[String, Any], round: Int, watches: Map[String, DMatrix] = Map(), metrics: Array[Array[Float]] = null, obj: ObjectiveTrait = null, eval: EvalTrait = null, earlyStoppingRound: Int = 0, booster: Booster = 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.

    metrics

    array containing the evaluation metrics for each matrix in watches for each iteration

    obj

    customized objective

    eval

    customized evaluation

    earlyStoppingRound

    if non-zero, training would be stopped after a specified number of consecutive increases in any evaluation metric.

    booster

    train from scratch if set to null; train from an existing booster if not null.

    returns

    The trained booster.

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    @throws( classOf[XGBoostError] )
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    (Since version ) see corresponding Javadoc for more information.

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