Object

org.emmalanguage.lib.ml.optimization.error

rmse

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object rmse extends Error

Root-Mean-Square Error (RMSE).

The root ensures that RMSE is measures on the same scale (and in the same units) as the target variable. This error function is usually used for evaluation and therefore we don't provide the gradient. For trainig the regular MSE works just as well.

loss: E(w) = sqrt { MSE } gradient: dE(w) = ???

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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[ID](weights: DVector, instances: DataBag[LDPoint[ID, Double]]): Double

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  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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  9. def finalize(): Unit

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

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  11. def gradient[ID](weights: DVector, instances: DataBag[LDPoint[ID, Double]]): DVector

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  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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  18. def toString(): String

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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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