compute_mse: Compute MSE - Mean Squared Error
In LGhilotti/CLLPackage: This package implements descend gradient and steepest descend methods for estimating linear model coefficients
compute_mse R Documentation
Compute MSE - Mean Squared Error
Description
Compute MSE - Mean Squared Error
Usage
compute_mse(y_observed, y_predicted)
Arguments
y_observed
[numeric] Observed values for the response variable
y_predicted
[numeric] Predicted values for the response variable
Value
[numeric] The MSE produced by the linear model
LGhilotti/CLLPackage documentation built on April 23, 2022, 3:48 a.m.
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| compute_mse | R Documentation |
Compute MSE - Mean Squared Error
Description
Compute MSE - Mean Squared Error
Usage
compute_mse(y_observed, y_predicted)
Arguments
y_observed |
[numeric] Observed values for the response variable |
y_predicted |
[numeric] Predicted values for the response variable |
Value
[numeric] The MSE produced by the linear model
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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