common

Type Members

1. class ArrayToTensor[T] extends Preprocessing[Seq[AnyVal], Tensor[T]]

   

   a Preprocessing that converts an Array[Double] or Array[Float] to a Tensor.

2. class BigDLAdapter[A, B] extends Preprocessing[A, B]

   

   Convert a BigDL Transformer to a Preprocessing

3. class ChainedPreprocessing[A, B, C] extends Preprocessing[A, C]

   

   chains two Preprocessing together.

   chains two Preprocessing together. The output type of the first Preprocessing should be the same with the input type of the second Preprocessing.

   A

   input type of the first Preprocessing

   B

   output type of the first Preprocessing, as well as the input type of the last Preprocessing

   C

   output of the last Preprocessing

4. class FeatureLabelPreprocessing[F, L, T] extends Preprocessing[(F, Option[L]), Sample[T]]

   

   construct a Preprocessing that convert (Feature, Label) tuple to a Sample.

   construct a Preprocessing that convert (Feature, Label) tuple to a Sample. The returned Preprocessing is robust for the case label = None, in which the Sample is derived from Feature only.

   F

   data type from feature column, E.g. Array[_] or Vector

   L

   data type from label column, E.g. Float, Double, Array[_] or Vector

5. trait Preprocessing[A, B] extends Transformer[A, B]

   

   Preprocessing defines data transform action during feature preprocessing.

   Preprocessing defines data transform action during feature preprocessing. Multiple Preprocessing can be combined into a ChainedPreprocessing. E.g., FeatureStep1[A, B] -> FeatureStep2[B, C] yield a ChainedFeatureSteps[A, C]

   A

   input data type

   B

   output data type

6. case class Relation(id1: String, id2: String, label: Int) extends Product with Serializable

   

   It represents the relationship between two items.

7. case class RelationPair(id1: String, id2Positive: String, id2Negative: String) extends Product with Serializable

   

   A relation pair is made up of two relations of the same id1: Relation(id1, id2Positive, label>0) [Positive Relation] Relation(id1, id2Negative, label=0) [Negative Relation]

8. class ScalarToTensor[T] extends Preprocessing[AnyVal, Tensor[T]]

   

   converts numbers to Tensors.

9. class SeqToTensor[T] extends Preprocessing[Any, Tensor[T]]

   

   a Preprocessing that converts Float, Double, Array[Float], Array[Double] or MLlib Vector to a Tensor.

10. class TensorToSample[T] extends Preprocessing[Tensor[T], Sample[T]]

    

    a Preprocessing that converts Tensor to Sample.

11. class ToTuple extends Preprocessing[Any, (Any, Option[Any])]

    

12. class TupleToFeatureAdapter[F, L, T] extends Preprocessing[(F, Option[L]), Sample[T]]

    

13. class MLlibVectorToTensor[T] extends Preprocessing[Vector, Tensor[T]]

    

    a Preprocessing that converts MLlib Vector to a Tensor.

    a Preprocessing that converts MLlib Vector to a Tensor. :: deprecated, NNEstimator can automatically extract Vectors now.

    Annotations

    @deprecated

    Deprecated

    (Since version 0.4.0) NNEstimator can automatically extract Vectors now