GLM

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. def LinLearner(mat0: Mat, targ: Mat): (Learner, LearnOptions)

   

5. object LinearLink extends GLMlink

   

6. object LinkEnum extends Enumeration

   

7. def LogLearner(mat0: Mat, targ: Mat): (Learner, LearnOptions)

   

8. object LogisticLink extends GLMlink

   

9. object MaxpLink extends GLMlink

   

10. object SVMLink extends GLMlink

    

11. def SVMlearner(mat0: Mat, targ: Mat, mat1: Mat, preds: Mat): (Learner, Learn12Options, Learner, Learn12Options)

    

12. def SVMlearner(mat0: Mat, targ: Mat): (Learner, Learn12Options)

    

13. def SVMpredictor(model: Model, mat1: Mat, preds: Mat): (Learner, LearnOptions)

    

14. final def asInstanceOf[T0]: T0

    

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15. def clone(): AnyRef

    

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16. def derivs(pred: Mat, targ: Mat, out: Mat, links: Mat, totflops: Long): Mat

    

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

    

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18. def equals(arg0: Any): Boolean

    

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19. def finalize(): Unit

    

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

    

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21. def hashCode(): Int

    

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22. def hashCross(a: Mat, b: Mat, c: Mat): Mat

    

23. def hashCross(a: GMat, b: GSMat, c: GSMat): GMat

    

24. def hashCrossT(a: Mat, b: Mat, c: Mat, nfeats: Int): Mat

    

25. def hashCrossT(a: GMat, b: GSMat, c: GSMat, nfeats: Int): GMat

    

26. def hashMult(a: Mat, b: Mat): Mat

    

27. def hashMult(a: GMat, b: GSMat): GMat

    

28. def hashMultT(a: Mat, b: Mat, nfeats: Int): Mat

    

29. def hashMultT(a: GMat, b: GSMat, nfeats: Int): GMat

    

30. final def isInstanceOf[T0]: Boolean

    

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31. def learnBatch(mat0: Mat, targ: Mat, d: Int): (Learner, LearnOptions)

    

32. def learnFPar(nstart: Int = FilesDS.encodeDate(2012,3,1,0), nend: Int = FilesDS.encodeDate(2012,12,1,0), d: Int = 0): (ParLearnerF, LearnFParOptions)

    

33. def learnFParx(nstart: Int = FilesDS.encodeDate(2012,3,1,0), nend: Int = FilesDS.encodeDate(2012,12,1,0), d: Int = 0): (ParLearnerxF, LearnFParOptions)

    

34. def learnPar(mat0: Mat, targ: Mat): (ParLearnerF, LearnParOptions)

    

35. def learnPar(mat0: Mat, targ: Mat, d: Int): (ParLearnerF, LearnParOptions)

    

36. def learnPar(mat0: Mat): (ParLearnerF, LearnParOptions)

    

37. def learnPar(mat0: Mat, d: Int): (ParLearnerF, LearnParOptions)

    

38. def learner(fnames: List[String]): (Learner, FGOptions)

    

39. def learner(ds: DataSource): (Learner, GOptions)

    

40. def learner(mat0: Mat, targ: Mat, mat1: Mat, preds: Mat, d: Int): (Learner, LearnOptions, Learner, LearnOptions)

    

41. def learner(mat0: Mat, targ: Mat, d: Int): (Learner, LearnOptions)

    

42. def learner(mat0: Mat): (Learner, LearnOptions)

    

43. def learner(mat0: Mat, d: Int = 0): (Learner, LearnOptions)

    

44. val linear: Int

    

45. val linkArray: Array[GLMlink]

    

46. def llfun(pred: Mat, targ: Mat, links: Mat, totflops: Long): Mat

    

47. val logistic: Int

    

48. val maxp: Int

    

49. def meanHelper(feta: FMat, fout: FMat, ilinks: IMat, istart: Int, iend: Int): Unit

    

50. def mkGLMModel(fopts: Model.Opts): GLM

    

51. def mkL1L2Regularizers(nopts: mixins.Mixin.Opts): Array[Mixin]

    

52. def mkL2Regularizer(nopts: mixins.Mixin.Opts): Array[Mixin]

    

53. def mkRegularizer(nopts: mixins.Mixin.Opts): Array[Mixin]

    

54. def mkUpdater(nopts: updaters.Updater.Opts): ADAGrad

    

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

    

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56. final def notify(): Unit

    

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57. final def notifyAll(): Unit

    

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58. def predictor(model: Model, mat1: Mat, preds: Mat, d: Int): (Learner, LearnOptions)

    

59. def preds(eta: Mat, out: Mat, links: Mat, totflops: Long): Mat

    

60. val svm: Int

    

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

    

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62. def toString(): String

    

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63. final def wait(): Unit

    

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

    

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

    

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