org.apache.spark.ml

DLClassifierModel

class DLClassifierModel[T] extends com.intel.analytics.bigdl.dlframes.DLClassifierModel[T]

Deprecated. Please refer to package com.intel.analytics.bigdl.dlframes.

DLClassifierModel is a specialized DLModel for classification tasks. The prediction column will have the datatype of Double.

Annotations
@deprecated
Deprecated

(Since version 0.5.0)

Linear Supertypes
com.intel.analytics.bigdl.dlframes.DLClassifierModel[T], com.intel.analytics.bigdl.dlframes.DLModel[T], DLParams[T], HasBatchSize, VectorCompatibility, HasPredictionCol, HasPredictionCol, HasFeaturesCol, HasFeaturesCol, DLTransformerBase[com.intel.analytics.bigdl.dlframes.DLModel[T]], Model[com.intel.analytics.bigdl.dlframes.DLModel[T]], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. DLClassifierModel
  2. DLClassifierModel
  3. DLModel
  4. DLParams
  5. HasBatchSize
  6. VectorCompatibility
  7. HasPredictionCol
  8. HasPredictionCol
  9. HasFeaturesCol
  10. HasFeaturesCol
  11. DLTransformerBase
  12. Model
  13. Transformer
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Instance Constructors

  1. new DLClassifierModel(model: Module[T], featureSize: Array[Int], uid: String = "DLClassifierModel")(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    model

    BigDL module to be optimized

    featureSize

    The size (Tensor dimensions) of the feature data.

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def $[T](param: Param[T]): T

    Attributes
    protected
    Definition Classes
    Params

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. final val batchSize: Param[Int]

    Definition Classes
    HasBatchSize

  9. final def clear(param: Param[_]): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  10. def clone(): AnyRef

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

  11. def copy(extra: ParamMap): com.intel.analytics.bigdl.dlframes.DLModel[T]

    Definition Classes
    DLModel → DLTransformerBase → Model → Transformer → PipelineStage → Params

  12. def copyValues[T <: Params](to: T, extra: ParamMap): T

    Attributes
    protected
    Definition Classes
    Params

  13. final def defaultCopy[T <: Params](extra: ParamMap): T

    Attributes
    protected
    Definition Classes
    Params

  14. final val endWhen: Param[Trigger]

    When to stop the training, passed in a Trigger.

    When to stop the training, passed in a Trigger. E.g. Trigger.maxIterations

    Definition Classes
    DLParams

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

    Definition Classes
    AnyRef

  16. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  17. def explainParam(param: Param[_]): String

    Definition Classes
    Params

  18. def explainParams(): String

    Definition Classes
    Params

  19. final def extractParamMap(): ParamMap

    Definition Classes
    Params

  20. final def extractParamMap(extra: ParamMap): ParamMap

    Definition Classes
    Params

  21. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  22. def finalize(): Unit

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

  23. final def get[T](param: Param[T]): Option[T]

    Definition Classes
    Params

  24. def getBatchSize: Int

    Definition Classes
    HasBatchSize

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

    Definition Classes
    AnyRef → Any

  26. def getConvertFunc(colType: DataType): (Row, Int) ⇒ Seq[AnyVal]

    Get conversion function to extract data from original DataFrame Default: 0

    Get conversion function to extract data from original DataFrame Default: 0

    Attributes
    protected
    Definition Classes
    DLParams

  27. final def getDefault[T](param: Param[T]): Option[T]

    Definition Classes
    Params

  28. def getEndWhen: Trigger

    Definition Classes
    DLParams

  29. def getFeatureSize: Array[Int]

    Definition Classes
    DLModel

  30. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

  31. def getLearningRate: Double

    Definition Classes
    DLParams

  32. def getLearningRateDecay: Double

    Definition Classes
    DLParams

  33. def getMaxEpoch: Int

    Definition Classes
    DLParams

  34. def getOptimMethod: OptimMethod[T]

    Definition Classes
    DLParams

  35. final def getOrDefault[T](param: Param[T]): T

    Definition Classes
    Params

  36. def getParam(paramName: String): Param[Any]

    Definition Classes
    Params

  37. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

  38. def getVectorSeq(row: Row, colType: DataType, index: Int): Seq[AnyVal]

    Definition Classes
    VectorCompatibility

  39. final def hasDefault[T](param: Param[T]): Boolean

    Definition Classes
    Params

  40. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  41. def hasParent: Boolean

    Definition Classes
    Model

  42. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  43. def internalTransform(dataFrame: DataFrame): DataFrame

    Perform a prediction on featureCol, and write result to the predictionCol.

    Perform a prediction on featureCol, and write result to the predictionCol.

    Attributes
    protected
    Definition Classes
    DLModel → DLTransformerBase

  44. final def isDefined(param: Param[_]): Boolean

    Definition Classes
    Params

  45. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  46. final def isSet(param: Param[_]): Boolean

    Definition Classes
    Params

  47. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  48. final val learningRate: DoubleParam

    learning rate for the optimizer in the DLEstimator.

    learning rate for the optimizer in the DLEstimator. Default: 0.001

    Definition Classes
    DLParams

  49. final val learningRateDecay: DoubleParam

    learning rate decay for each iteration.

    learning rate decay for each iteration. Default: 0

    Definition Classes
    DLParams

  50. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

  51. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  52. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  53. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  54. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  55. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  56. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  57. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

  58. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  59. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  60. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  61. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  62. final val maxEpoch: IntParam

    Number of max Epoch for the training, an epoch refers to a traverse over the training data Default: 50

    Number of max Epoch for the training, an epoch refers to a traverse over the training data Default: 50

    Definition Classes
    DLParams

  63. val model: Module[T]

    BigDL module to be optimized

    BigDL module to be optimized

    Definition Classes
    DLClassifierModel → DLClassifierModel → DLModel

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

    Definition Classes
    AnyRef

  65. final def notify(): Unit

    Definition Classes
    AnyRef

  66. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  67. final val optimMethod: Param[OptimMethod[T]]

    optimization method to be used.

    optimization method to be used. BigDL supports many optimization methods like Adam, SGD and LBFGS. Refer to package com.intel.analytics.bigdl.optim for all the options. Default: SGD

    Definition Classes
    DLParams

  68. def outputToPrediction(output: Tensor[T]): Any

    Attributes
    protected
    Definition Classes
    DLClassifierModel → DLModel

  69. lazy val params: Array[Param[_]]

    Definition Classes
    Params

  70. var parent: Estimator[com.intel.analytics.bigdl.dlframes.DLModel[T]]

    Definition Classes
    Model

  71. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  72. final def set(paramPair: ParamPair[_]): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  73. final def set(param: String, value: Any): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  74. final def set[T](param: Param[T], value: T): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  75. def setBatchSize(value: Int): DLClassifierModel.this.type

    Definition Classes
    DLModel

  76. final def setDefault(paramPairs: ParamPair[_]*): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  77. final def setDefault[T](param: Param[T], value: T): DLClassifierModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  78. def setFeatureSize(value: Array[Int]): DLClassifierModel.this.type

    Definition Classes
    DLModel

  79. def setFeaturesCol(featuresColName: String): DLClassifierModel.this.type

    Definition Classes
    DLModel

  80. def setParent(parent: Estimator[com.intel.analytics.bigdl.dlframes.DLModel[T]]): com.intel.analytics.bigdl.dlframes.DLModel[T]

    Definition Classes
    Model

  81. def setPredictionCol(value: String): DLClassifierModel.this.type

    Definition Classes
    DLModel

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

    Definition Classes
    AnyRef

  83. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  84. def transform(dataFrame: DataFrame): DataFrame

    Definition Classes
    DLTransformerBase → Transformer

  85. def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame

    Definition Classes
    Transformer

  86. def transform(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    Definition Classes
    Transformer
    Annotations
    @varargs()

  87. def transformSchema(schema: StructType): StructType

    Definition Classes
    DLClassifierModel → DLModel → PipelineStage

  88. def transformSchema(schema: StructType, logging: Boolean): StructType

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  89. val uid: String

    Definition Classes
    DLClassifierModel → DLClassifierModel → DLModel → Identifiable

  90. val validVectorTypes: Seq[VectorUDT]

    Definition Classes
    VectorCompatibility

  91. def validateDataType(schema: StructType, colName: String): Unit

    Validate if feature and label columns are of supported data types.

    Validate if feature and label columns are of supported data types. Default: 0

    Attributes
    protected
    Definition Classes
    DLParams

  92. def validateParams(): Unit

    Definition Classes
    Params

  93. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from com.intel.analytics.bigdl.dlframes.DLClassifierModel[T]

Inherited from com.intel.analytics.bigdl.dlframes.DLModel[T]

Inherited from DLParams[T]

Inherited from HasBatchSize

Inherited from VectorCompatibility

Inherited from HasPredictionCol

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasFeaturesCol

Inherited from DLTransformerBase[com.intel.analytics.bigdl.dlframes.DLModel[T]]

Inherited from Model[com.intel.analytics.bigdl.dlframes.DLModel[T]]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped