Class

com.intel.analytics.zoo.models.recommendation

ColumnFeatureInfo

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case class ColumnFeatureInfo(wideBaseCols: Array[String] = Array[String](), wideBaseDims: Array[Int] = Array[Int](), wideCrossCols: Array[String] = Array[String](), wideCrossDims: Array[Int] = Array[Int](), indicatorCols: Array[String] = Array[String](), indicatorDims: Array[Int] = Array[Int](), embedCols: Array[String] = Array[String](), embedInDims: Array[Int] = Array[Int](), embedOutDims: Array[Int] = Array[Int](), continuousCols: Array[String] = Array[String](), label: String = "label") extends Serializable with Product

The same data information shared by the WideAndDeep model and its feature generation part.

wideBaseCols

Data of wideBaseCols together with wideCrossCols will be fed into the wide model.

wideBaseDims

Dimensions of wideBaseCols. The dimensions of the data in wideBaseCols should be within the range of wideBaseDims.

wideCrossCols

Data of wideCrossCols will be fed into the wide model.

wideCrossDims

Dimensions of wideCrossCols. The dimensions of the data in wideCrossCols should be within the range of wideCrossDims.

indicatorCols

Data of indicatorCols will be fed into the deep model as multi-hot vectors.

indicatorDims

Dimensions of indicatorCols. The dimensions of the data in indicatorCols should be within the range of indicatorDims.

embedCols

Data of embedCols will be fed into the deep model as embeddings.

embedInDims

Input dimension of the data in embedCols. The dimensions of the data in embedCols should be within the range of embedInDims.

embedOutDims

The dimensions of embeddings.

continuousCols

Data of continuousCols will be treated as continuous values for the deep model.

label

The name of the 'label' column. Default is 'label'.

Linear Supertypes
Product, Equals, Serializable, Serializable, AnyRef, Any
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  1. ColumnFeatureInfo
  2. Product
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Instance Constructors

  1. new ColumnFeatureInfo(wideBaseCols: Array[String] = Array[String](), wideBaseDims: Array[Int] = Array[Int](), wideCrossCols: Array[String] = Array[String](), wideCrossDims: Array[Int] = Array[Int](), indicatorCols: Array[String] = Array[String](), indicatorDims: Array[Int] = Array[Int](), embedCols: Array[String] = Array[String](), embedInDims: Array[Int] = Array[Int](), embedOutDims: Array[Int] = Array[Int](), continuousCols: Array[String] = Array[String](), label: String = "label")

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    wideBaseCols

    Data of wideBaseCols together with wideCrossCols will be fed into the wide model.

    wideBaseDims

    Dimensions of wideBaseCols. The dimensions of the data in wideBaseCols should be within the range of wideBaseDims.

    wideCrossCols

    Data of wideCrossCols will be fed into the wide model.

    wideCrossDims

    Dimensions of wideCrossCols. The dimensions of the data in wideCrossCols should be within the range of wideCrossDims.

    indicatorCols

    Data of indicatorCols will be fed into the deep model as multi-hot vectors.

    indicatorDims

    Dimensions of indicatorCols. The dimensions of the data in indicatorCols should be within the range of indicatorDims.

    embedCols

    Data of embedCols will be fed into the deep model as embeddings.

    embedInDims

    Input dimension of the data in embedCols. The dimensions of the data in embedCols should be within the range of embedInDims.

    embedOutDims

    The dimensions of embeddings.

    continuousCols

    Data of continuousCols will be treated as continuous values for the deep model.

    label

    The name of the 'label' column. Default is 'label'.

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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )

  6. val continuousCols: Array[String]

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    Data of continuousCols will be treated as continuous values for the deep model.

  7. val embedCols: Array[String]

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    Data of embedCols will be fed into the deep model as embeddings.

  8. val embedInDims: Array[Int]

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    Input dimension of the data in embedCols.

    Input dimension of the data in embedCols. The dimensions of the data in embedCols should be within the range of embedInDims.

  9. val embedOutDims: Array[Int]

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    The dimensions of embeddings.

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

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    AnyRef

  11. def finalize(): Unit

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

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

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  13. val indicatorCols: Array[String]

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    Data of indicatorCols will be fed into the deep model as multi-hot vectors.

  14. val indicatorDims: Array[Int]

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    Dimensions of indicatorCols.

    Dimensions of indicatorCols. The dimensions of the data in indicatorCols should be within the range of indicatorDims.

  15. final def isInstanceOf[T0]: Boolean

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    Any

  16. val label: String

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    The name of the 'label' column.

    The name of the 'label' column. Default is 'label'.

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

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    AnyRef

  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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    AnyRef

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

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  21. final def wait(): Unit

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    @throws( ... )

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

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

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  24. val wideBaseCols: Array[String]

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    Data of wideBaseCols together with wideCrossCols will be fed into the wide model.

  25. val wideBaseDims: Array[Int]

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    Dimensions of wideBaseCols.

    Dimensions of wideBaseCols. The dimensions of the data in wideBaseCols should be within the range of wideBaseDims.

  26. val wideCrossCols: Array[String]

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    Data of wideCrossCols will be fed into the wide model.

  27. val wideCrossDims: Array[Int]

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    Dimensions of wideCrossCols.

    Dimensions of wideCrossCols. The dimensions of the data in wideCrossCols should be within the range of wideCrossDims.

Inherited from Product

Inherited from Equals

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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