class RegressionTreeResult extends PredictionResult[Double]
Simple wrapper around a sequence of predictions
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- new RegressionTreeResult(predictions: Seq[(PredictionResult[Double], TreeMeta)])
- predictions
sequence of predictions
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- def getDepth(): Seq[Int]
- def getExpected(): Seq[Double]
Get the predictions
Get the predictions
- returns
expected value of each prediction
- Definition Classes
- RegressionTreeResult → PredictionResult
- def getGradient(): Option[Seq[Vector[Double]]]
Get the gradient or sensitivity of each prediction
Get the gradient or sensitivity of each prediction
- returns
a vector of doubles for each prediction
- Definition Classes
- RegressionTreeResult → PredictionResult
- def getImportanceScores(): Option[Seq[Seq[Double]]]
Get the training row scores for each prediction
Get the training row scores for each prediction
- returns
sequence (over predictions) of sequence (over training rows) of importances
- Definition Classes
- PredictionResult
- def getInfluenceScores(actuals: Seq[Any]): Option[Seq[Seq[Double]]]
Get the improvement (positive) or damage (negative) due to each training row on a prediction
Get the improvement (positive) or damage (negative) due to each training row on a prediction
- actuals
to assess the improvement or damage against
- returns
Sequence (over predictions) of sequence (over training rows) of influence
- Definition Classes
- PredictionResult
- def getUncertainty(observational: Boolean = true): Option[Seq[Any]]
Get the "uncertainty" of the prediction
Get the "uncertainty" of the prediction
For regression, this should be the TotalError if non-observational and the StdDevObs if observational
- observational
whether the uncertainty should account for observational uncertainty
- returns
uncertainty of each prediction
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- PredictionResult
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