NRMSE: Normalised Root Mean Squared Error
In PerMat: Performance Metrics in Predictive Modeling
NRMSE R Documentation
Normalised Root Mean Squared Error
Description
Normalised Root Mean Squared Error
Usage
NRMSE(actual, predicted)
Arguments
actual
Actual value of the target variable
predicted
Predicted value of the target variable
Value
NRMSE of the fitted model
Examples
actual <- c(100, 150, 200, 250, 300, 350, 400, 450, 500, 550)
predicted <- c(95, 148, 210, 245, 290, 360, 395, 440, 510, 540)
NRMSE(actual, predicted)
PerMat documentation built on June 22, 2024, 10:55 a.m.
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| NRMSE | R Documentation |
Normalised Root Mean Squared Error
Description
Normalised Root Mean Squared Error
Usage
NRMSE(actual, predicted)
Arguments
actual |
Actual value of the target variable |
predicted |
Predicted value of the target variable |
Value
NRMSE of the fitted model
Examples
actual <- c(100, 150, 200, 250, 300, 350, 400, 450, 500, 550)
predicted <- c(95, 148, 210, 245, 290, 360, 395, 440, 510, 540)
NRMSE(actual, predicted)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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