class MultiTaskStandardizerTrainingResult extends MultiTaskTrainingResult
Training result wrapping the base learner's training result next to the transformations
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- MultiTaskTrainingResult
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- new MultiTaskStandardizerTrainingResult(baseTrainingResult: MultiTaskTrainingResult, outputTrans: Seq[Option[Standardization]], inputTrans: Seq[Option[Standardization]])
- baseTrainingResult
result of training on the standardized inputs and output
- outputTrans
optional sequence of transformation (rescale, offset) of output labels
- inputTrans
sequence of optional transformations (rescale, offset) of inputs
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- def getFeatureImportance(): Option[Vector[Double]]
Get a measure of the importance of the model features
Get a measure of the importance of the model features
- returns
feature influences as an array of doubles
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- MultiTaskStandardizerTrainingResult → TrainingResult
- def getLoss(): Option[Double]
Get a measure of the loss of the model, e.g.
Get a measure of the loss of the model, e.g. RMS OOB error
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- TrainingResult
- def getModel(): MultiTaskModel
Get the model contained in the training result
Get the model contained in the training result
- returns
the model
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- MultiTaskStandardizerTrainingResult → MultiTaskTrainingResult → TrainingResult
- def getModels(): Seq[Model[PredictionResult[Any]]]
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- MultiTaskStandardizerTrainingResult → MultiTaskTrainingResult
- def getPredictedVsActual(): Option[Seq[(Vector[Any], Seq[Option[Any]], Seq[Option[Any]])]]
Get the predicted vs actual values, e.g.
Get the predicted vs actual values, e.g. from OOB
- returns
seq of (feature vector, predicted value, and actual value)
- Definition Classes
- MultiTaskStandardizerTrainingResult → MultiTaskTrainingResult → TrainingResult
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