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com.intel.analytics.zoo.models.recommendation

WideAndDeep

Related Docs: class WideAndDeep | package recommendation

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object WideAndDeep extends Serializable

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  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. def apply[T](modelType: String = "wide_n_deep", numClasses: Int, columnInfo: ColumnFeatureInfo, hiddenLayers: Array[Int] = Array(40, 20, 10))(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): WideAndDeep[T]

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    The factory method to create a WideAndDeep instance.

    The factory method to create a WideAndDeep instance.

    modelType

    String. "wide", "deep", "wide_n_deep" are supported. Default is "wide_n_deep".

    numClasses

    The number of classes. Positive integer.

    columnInfo

    An instance of ColumnFeatureInfo.

    hiddenLayers

    Units of hidden layers for the deep model. Array of positive integers. Default is Array(40, 20, 10).

  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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  9. def finalize(): Unit

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

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  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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  13. def loadModel[T](path: String, weightPath: String = null)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): WideAndDeep[T]

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    Load an existing WideAndDeep model (with weights).

    Load an existing WideAndDeep model (with weights).

    T

    Numeric type of parameter(e.g. weight, bias). Only support float/double now.

    path

    The path for the pre-defined model. Local file system, HDFS and Amazon S3 are supported. HDFS path should be like "hdfs://[host]:[port]/xxx". Amazon S3 path should be like "s3a://bucket/xxx".

    weightPath

    The path for pre-trained weights if any. Default is null.

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  19. final def wait(): Unit

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

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

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