Packages

class Booster extends Serializable with KryoSerializable

Booster for xgboost, this is a model API that support interactive build of a XGBoost Model

DEVELOPER WARNING: A Java Booster must not be shared by more than one Scala Booster

Linear Supertypes
KryoSerializable, Serializable, Serializable, AnyRef, Any
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  1. Booster
  2. KryoSerializable
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
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Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def boost(dtrain: DMatrix, grad: Array[Float], hess: Array[Float]): Unit

    update with give grad and hess

    update with give grad and hess

    dtrain

    training data

    grad

    first order of gradient

    hess

    seconde order of gradient

    Annotations
    @throws( classOf[XGBoostError] )
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. def dispose: Unit

    Dispose the booster when it is no longer needed

  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: EvalTrait): String

    evaluate with given customized Evaluation class

    evaluate with given customized Evaluation class

    evalMatrixs

    evaluation matrix

    evalNames

    evaluation names

    eval

    custom evaluator

    returns

    eval information

    Annotations
    @throws( classOf[XGBoostError] )
  11. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], iter: Int): String

    evaluate with given dmatrixs.

    evaluate with given dmatrixs.

    evalMatrixs

    dmatrixs for evaluation

    evalNames

    name for eval dmatrixs, used for check results

    iter

    current eval iteration

    returns

    eval information

    Annotations
    @throws( classOf[XGBoostError] )
  12. def finalize(): Unit
    Definition Classes
    Booster → AnyRef
  13. def getAttr(key: String): String

    Get attribute from the Booster.

    Get attribute from the Booster.

    key

    attr name

    returns

    attr value

    Annotations
    @throws( classOf[XGBoostError] )
  14. def getAttrs: Map[String, String]

    Get attributes stored in the Booster as a Map.

    Get attributes stored in the Booster as a Map.

    returns

    A map contain attribute pairs.

    Annotations
    @throws( classOf[XGBoostError] )
  15. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. def getFeatureScore(featureNames: Array[String]): Map[String, Integer]

    Get importance of each feature based on weight only (number of splits), with specified feature names.

    Get importance of each feature based on weight only (number of splits), with specified feature names.

    returns

    featureScoreMap key: feature name, value: feature importance score

    Annotations
    @throws( classOf[XGBoostError] )
  17. def getFeatureScore(featureMap: String = null): Map[String, Integer]

    Get importance of each feature based on weight only (number of splits)

    Get importance of each feature based on weight only (number of splits)

    returns

    featureScoreMap key: feature index, value: feature importance score

    Annotations
    @throws( classOf[XGBoostError] )
  18. def getModelDump(featureNames: Array[String], withStats: Boolean, format: String): Array[String]
  19. def getModelDump(featureNames: Array[String]): Array[String]

    Dump model as Array of string with specified feature names.

    Dump model as Array of string with specified feature names.

    featureNames

    Names of features.

    Annotations
    @throws( classOf[XGBoostError] )
  20. def getModelDump(featureMap: String = null, withStats: Boolean = false, format: String = "text"): Array[String]

    Dump model as Array of string

    Dump model as Array of string

    featureMap

    featureMap file

    withStats

    bool Controls whether the split statistics are output.

    Annotations
    @throws( classOf[XGBoostError] )
  21. def getScore(featureNames: Array[String], importanceType: String): Map[String, Double]

    Get importance of each feature based on information gain or cover , with specified feature names.

    Get importance of each feature based on information gain or cover , with specified feature names. Supported: ["gain, "cover", "total_gain", "total_cover"]

    returns

    featureScoreMap key: feature name, value: feature importance score

    Annotations
    @throws( classOf[XGBoostError] )
  22. def getScore(featureMap: String, importanceType: String): Map[String, Double]

    Get importance of each feature based on information gain or cover Supported: ["gain, "cover", "total_gain", "total_cover"]

    Get importance of each feature based on information gain or cover Supported: ["gain, "cover", "total_gain", "total_cover"]

    returns

    featureScoreMap key: feature index, value: feature importance score

    Annotations
    @throws( classOf[XGBoostError] )
  23. def getVersion: Int
  24. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  25. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  26. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  28. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  29. def predict(data: DMatrix, outPutMargin: Boolean = false, treeLimit: Int = 0): Array[Array[Float]]

    Predict with data

    Predict with data

    data

    dmatrix storing the input

    outPutMargin

    Whether to output the raw untransformed margin value.

    treeLimit

    Limit number of trees in the prediction; defaults to 0 (use all trees).

    returns

    predict result

    Annotations
    @throws( classOf[XGBoostError] )
  30. def predictContrib(data: DMatrix, treeLimit: Int = 0): Array[Array[Float]]

    Output feature contributions toward predictions of given data

    Output feature contributions toward predictions of given data

    data

    dmatrix storing the input

    treeLimit

    Limit number of trees in the prediction; defaults to 0 (use all trees).

    returns

    The feature contributions and bias.

    Annotations
    @throws( classOf[XGBoostError] )
    Exceptions thrown

    XGBoostError native error

  31. def predictLeaf(data: DMatrix, treeLimit: Int = 0): Array[Array[Float]]

    Predict the leaf indices

    Predict the leaf indices

    data

    dmatrix storing the input

    treeLimit

    Limit number of trees in the prediction; defaults to 0 (use all trees).

    returns

    predict result

    Annotations
    @throws( classOf[XGBoostError] )
    Exceptions thrown

    XGBoostError native error

  32. def read(kryo: Kryo, input: Input): Unit
    Definition Classes
    Booster → KryoSerializable
  33. def saveModel(out: OutputStream): Unit

    save model to Output stream

    save model to Output stream

    out

    Output stream

    Annotations
    @throws( classOf[XGBoostError] )
  34. def saveModel(modelPath: String): Unit

    save model to modelPath

    save model to modelPath

    modelPath

    model path

    Annotations
    @throws( classOf[XGBoostError] )
  35. def setAttr(key: String, value: String): Unit

    Set attribute to the Booster.

    Set attribute to the Booster.

    key

    attr name

    value

    attr value

    Annotations
    @throws( classOf[XGBoostError] )
  36. def setAttrs(params: Map[String, String]): Unit

    set attributes

    set attributes

    params

    attributes key-value map

    Annotations
    @throws( classOf[XGBoostError] )
  37. def setParam(key: String, value: AnyRef): Unit

    Set parameter to the Booster.

    Set parameter to the Booster.

    key

    param name

    value

    param value

    Annotations
    @throws( classOf[XGBoostError] )
  38. def setParams(params: Map[String, AnyRef]): Unit

    set parameters

    set parameters

    params

    parameters key-value map

    Annotations
    @throws( classOf[XGBoostError] )
  39. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  40. def toByteArray: Array[Byte]
  41. def toString(): String
    Definition Classes
    AnyRef → Any
  42. def update(dtrain: DMatrix, obj: ObjectiveTrait): Unit

    update with customize obj func

    update with customize obj func

    dtrain

    training data

    obj

    customized objective class

    Annotations
    @throws( classOf[XGBoostError] )
  43. def update(dtrain: DMatrix, iter: Int): Unit

    Update (one iteration)

    Update (one iteration)

    dtrain

    training data

    iter

    current iteration number

    Annotations
    @throws( classOf[XGBoostError] )
  44. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  45. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  46. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  47. def write(kryo: Kryo, output: Output): Unit
    Definition Classes
    Booster → KryoSerializable

Inherited from KryoSerializable

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped