DeepLearningSupport

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. def DLModel[T <: Frame](train: T, valid: T, response: String, modelId: String = "model", epochs: Int = 10, l1: Double = 0.0001, l2: Double = 0.0001, activation: Activation = Activation.RectifierWithDropout, hidden: Array[Int] = Array(200, 200)): DeepLearningModel

   

   Create Deep Learning Model for the basic usage.

   Create Deep Learning Model for the basic usage. This method exposes the basic configuration of the model. If you need to specify some arguments which are not exposed, please use the DeepLearning model via Sparkling Water pipelines API or using the raw java API

   T

   H2O Frame Type

   train

   frame to train

   valid

   validation frame

   response

   response column

   modelId

   name of the model

   epochs

   number of epochs

   l1

   l1 regularization

   l2

   l2 regularization

   activation

   activation function

   hidden

   number and size of the hidden layers

   returns

   Deep Learning Model

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   DeepLearningSupport

5. final def asInstanceOf[T0]: T0

   

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6. def clone(): AnyRef

   

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

   

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8. def equals(arg0: Any): Boolean

   

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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. final def ne(arg0: AnyRef): Boolean

    

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14. final def notify(): Unit

    

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15. final def notifyAll(): Unit

    

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

    

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17. def toString(): String

    

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18. final def wait(): Unit

    

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

    

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

    

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