loss_MSE_math: Mean Squared Error (symbolic function)
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R
Description
Usage
Arguments
Details
Value
Examples
Description
This function computes the Mean Squared Error loss (MSE) per value provided x (preds - labels).
Usage
1
loss_MSE_math(x, y)
Arguments
x
The predictions.
y
The labels.
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The Squared Error per value.
Examples
1
2
3
4
## Not run:
SymbolicLoss(fc = loss_MSE_math)
## End(Not run)
Laurae2/Laurae documentation built on May 8, 2019, 7:59 p.m.
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Description Usage Arguments Details Value Examples
Description
This function computes the Mean Squared Error loss (MSE) per value provided x (preds - labels).
Usage
1 | loss_MSE_math(x, y)
|
Arguments
x |
The |
y |
The |
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The Squared Error per value.
Examples
1 2 3 4 | ## Not run:
SymbolicLoss(fc = loss_MSE_math)
## End(Not run)
|
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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