case class StandardError(rescale: Double = 1.0) extends Merit[Double] with Product with Serializable
Root mean square of (the error divided by the predicted uncertainty)
Linear Supertypes
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- new StandardError(rescale: Double = 1.0)
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- def estimate(pva: Iterable[(PredictionResult[Double], Seq[Double])], rng: Random = Random): (Double, Double)
Estimate the merit and the uncertainty in the merit over batches of predicted and ground-truth values
Estimate the merit and the uncertainty in the merit over batches of predicted and ground-truth values
- pva
predicted-vs-actual data as an iterable over PredictionResult and ground-truth tuples
- returns
the estimate of the merit value and the uncertainty in that estimate
- Definition Classes
- Merit
- def evaluate(predictionResult: PredictionResult[Double], actual: Seq[Double], rng: Random = Random): Double
Apply the figure of merti to a prediction result and set of ground-truth values
Apply the figure of merti to a prediction result and set of ground-truth values
- returns
the value of the figure of merit
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