NNEstimator

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. def apply[F, T](model: Module[T], criterion: Criterion[T], featurePreprocessing: Preprocessing[F, Sample[T]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): NNEstimator[T]

   

   Construct a NNEstimator with a featurePreprocessing only.

   Construct a NNEstimator with a featurePreprocessing only. The constructor is useful when both feature and label are derived from the same column of the original DataFrame.

   model

   BigDL module to be optimized

   criterion

   BigDL criterion method

   featurePreprocessing

   A Preprocessing that transforms the feature data to a Sample[T].

5. def apply[F, L, T](model: Module[T], criterion: Criterion[T], featurePreprocessing: Preprocessing[F, Tensor[T]], labelPreprocessing: Preprocessing[L, Tensor[T]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): NNEstimator[T]

   

   Construct a NNEstimator with a feature Preprocessing and label Preprocessing.

   Construct a NNEstimator with a feature Preprocessing and label Preprocessing.

   model

   BigDL module to be optimized

   criterion

   BigDL criterion method

   featurePreprocessing

   Preprocessing[Any, Tensor[T] ]

   labelPreprocessing

   Preprocessing[Any, Tensor[T] ]

6. def apply[T](model: Module[T], criterion: Criterion[T], featureSize: Array[Int], labelSize: Array[Int])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): NNEstimator[T]

   

   Construct a NNEstimator with a feature size and label size.

   Construct a NNEstimator with a feature size and label size. The constructor is useful when the feature column and label column contains the following data types: Float, Double, Int, Array[Float], Array[Double], Array[Int] and MLlib Vector. The feature and label data are converted to Tensors with the specified sizes before sending to the model.

   model

   BigDL module to be optimized

   criterion

   BigDL criterion method

   featureSize

   The size (Tensor dimensions) of the feature data. e.g. an image may be with width * height = 28 * 28, featureSize = Array(28, 28).

   labelSize

   The size (Tensor dimensions) of the label data.

7. def apply[T](model: Module[T], criterion: Criterion[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): NNEstimator[T]

   

   Construct a NNEstimator with default Preprocessing: A SeqToTensor

   Construct a NNEstimator with default Preprocessing: A SeqToTensor

   model

   BigDL module to be optimized

   criterion

   BigDL criterion method

8. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

9. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

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

    

    Definition Classes

    AnyRef

11. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

12. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

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

    

    Definition Classes

    AnyRef → Any

14. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

15. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

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

    

    Definition Classes

    AnyRef

17. final def notify(): Unit

    

    Definition Classes

    AnyRef

18. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

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

    

    Definition Classes

    AnyRef

20. def toString(): String

    

    Definition Classes

    AnyRef → Any

21. final def wait(): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )