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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 boost(dtrain: DMatrix, grad: Array[Float], hess: Array[Float]): Unit

   

6. def clone(): AnyRef

   

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7. def dispose(): Unit

   

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

   

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9. def equals(arg0: Any): Boolean

   

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10. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation, metricsOut: Array[Float]): String

    

11. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation): String

    

12. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], iter: Int, metricsOut: Array[Float]): String

    

13. def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], iter: Int): String

    

14. def finalize(): Unit

    

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15. final def getAttr(key: String): String

    

16. final def getAttrs(): Map[String, String]

    

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

    

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18. def getFeatureScore(featureMap: String): Map[String, Integer]

    

19. def getFeatureScore(featureNames: Array[String]): Map[String, Integer]

    

20. def getModelDump(featureNames: Array[String], withStats: Boolean, format: String): Array[String]

    

21. def getModelDump(featureNames: Array[String], withStats: Boolean): Array[String]

    

22. def getModelDump(featureMap: String, withStats: Boolean, format: String): Array[String]

    

23. def getModelDump(featureMap: String, withStats: Boolean): Array[String]

    

24. def getScore(featureMap: String, importanceType: String): Map[String, Double]

    

25. def getScore(featureNames: Array[String], importanceType: String): Map[String, Double]

    

26. def getVersion(): Int

    

27. def hashCode(): Int

    

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28. final def isInstanceOf[T0]: Boolean

    

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

    

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30. final def notify(): Unit

    

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31. final def notifyAll(): Unit

    

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32. def predict(data: DMatrix, outputMargin: Boolean, treeLimit: Int): Array[Array[Float]]

    

33. def predict(data: DMatrix, outputMargin: Boolean): Array[Array[Float]]

    

34. def predict(data: DMatrix): Array[Array[Float]]

    

35. def predictContrib(data: DMatrix, treeLimit: Int): Array[Array[Float]]

    

36. def predictLeaf(data: DMatrix, treeLimit: Int): Array[Array[Float]]

    

37. def read(kryo: Kryo, input: Input): Unit

    

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38. def saveModel(out: OutputStream): Unit

    

39. def saveModel(modelPath: String): Unit

    

40. final def setAttr(key: String, value: String): Unit

    

41. def setAttrs(attrs: Map[String, String]): Unit

    

42. final def setParam(key: String, value: Any): Unit

    

43. def setParams(params: Map[String, AnyRef]): Unit

    

44. def setVersion(version: Int): Unit

    

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

    

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46. def toByteArray(): Array[Byte]

    

47. def toString(): String

    

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48. def update(dtrain: DMatrix, obj: IObjective): Unit

    

49. def update(dtrain: DMatrix, iter: Int): Unit

    

50. final def wait(): Unit

    

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

    

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

    

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53. def write(kryo: Kryo, output: Output): Unit

    

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