Class

com.tencent.angel.ml.classification

SoftmaxRegression

Related Doc: package classification

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class SoftmaxRegression extends AngelModel

LR model

Linear Supertypes
AngelModel, GraphModel, MLModel, AnyRef, Any
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Inherited
  1. SoftmaxRegression
  2. AngelModel
  3. GraphModel
  4. MLModel
  5. AnyRef
  6. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SoftmaxRegression(conf: SharedConf, _ctx: TaskContext = null)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. def addVariable(variable: Variable): SoftmaxRegression.this.type

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    Definition Classes
    GraphModel → MLModel

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. lazy val batchSize: Int

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    Definition Classes
    AngelModel

  7. lazy val blockSize: Int

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    Definition Classes
    AngelModel

  8. def buildNetwork(): SoftmaxRegression.this.type

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    Definition Classes
    SoftmaxRegression → AngelModel → GraphModel

  9. implicit val cilsImpl: CILSImpl

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    Attributes
    protected
    Definition Classes
    AngelModel

  10. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  11. val conf: SharedConf

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    Definition Classes
    MLModel

  12. def createMatrices[T](envCtx: EnvContext[T]): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  13. val dataFormat: String

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    Definition Classes
    MLModel

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

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    Definition Classes
    AnyRef

  15. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  16. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  17. def getAllGradients: Map[String, Matrix]

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    Definition Classes
    MLModel

  18. def getAllSlots: Map[String, Matrix]

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    Definition Classes
    MLModel

  19. def getAllVariables: List[Variable]

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    Definition Classes
    MLModel

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

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    Definition Classes
    AnyRef → Any

  21. def getGradient(name: String): Matrix

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    Definition Classes
    MLModel

  22. def getSlot(name: String): Matrix

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    Definition Classes
    MLModel

  23. def getVariable(name: String): Variable

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    Definition Classes
    MLModel

  24. implicit lazy val graph: Graph

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    Definition Classes
    AngelModel → GraphModel

  25. def hasGradient(name: String): Boolean

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    Definition Classes
    MLModel

  26. def hasSlot(name: String): Boolean

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    Definition Classes
    MLModel

  27. def hasVariable(name: String): Boolean

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    Definition Classes
    MLModel

  28. def hasVariable(v: Variable): Boolean

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    Definition Classes
    MLModel

  29. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  30. val indexRange: Long

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    Definition Classes
    MLModel

  31. def init[T](envCtx: EnvContext[T], taskId: Int): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  32. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  33. val isSparseFormat: Boolean

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    Definition Classes
    MLModel

  34. def keyType: String

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    Definition Classes
    MLModel

  35. def loadModel[T](envCtx: EnvContext[T], path: String, conf: Configuration): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  36. def lossFunc: LossFunc

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    Definition Classes
    GraphModel

  37. val modelType: RowType

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    Definition Classes
    MLModel

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

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    Definition Classes
    AnyRef

  39. final def notify(): Unit

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    Definition Classes
    AnyRef

  40. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  41. val numClass: Int

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  42. val optProvider: PSOptimizerProvider

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  43. def predict(storage: LabeledData): PredictResult

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    Definition Classes
    AngelModel → MLModel

  44. def predict(storage: DataBlock[LabeledData]): List[PredictResult]

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    Predict use the PSModels and predict data

    Predict use the PSModels and predict data

    storage

    predict data

    returns

    predict result

    Definition Classes
    AngelModel → MLModel

  45. def pullParams(epoch: Int, indices: Vector): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  46. def pushGradient(lr: Double): Unit

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    Definition Classes
    GraphModel

  47. def pushSlot(lr: Double): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  48. def putGradient(v: Variable, g: Matrix): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  49. def putSlot(v: Variable, g: Matrix): SoftmaxRegression.this.type

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    Definition Classes
    GraphModel → MLModel

  50. def releaseMode[T](envCtx: EnvContext[T]): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  51. def saveModel[T](envCtx: EnvContext[T], path: String): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  52. def setState(state: VarState): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  53. def storageType: String

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    Definition Classes
    MLModel

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

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    Definition Classes
    AnyRef

  55. var taskNum: Int

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    Definition Classes
    AngelModel

  56. def toString(): String

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    Definition Classes
    AnyRef → Any

  57. def update[T](epoch: Int, batchSize: Int): SoftmaxRegression.this.type

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    Definition Classes
    MLModel

  58. def updateConf(newConf: SharedConf): SoftmaxRegression.this.type

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    Definition Classes
    GraphModel

  59. val validIndexNum: Long

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    Definition Classes
    MLModel

  60. def valueType: String

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    Definition Classes
    MLModel

  61. implicit val variableManager: VariableManager

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    Attributes
    protected
    Definition Classes
    AngelModel → MLModel

  62. val variableProvider: VariableProvider

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    Attributes
    protected
    Definition Classes
    AngelModel → MLModel

  63. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from AngelModel

Inherited from GraphModel

Inherited from MLModel

Inherited from AnyRef

Inherited from Any

Ungrouped