loss_MCE: Mean Cubic Error (computation function)
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R
Description
Usage
Arguments
Details
Value
Description
This function computes the Mean Cubic Error loss (MCE) per value provided preds and labels.
Usage
1
loss_MCE(y_pred, y_true)
Arguments
y_pred
The predictions.
y_true
The labels.
Details
Supposing: x = preds - labels
Loss Formula : abs(x^3)
Gradient Formula : 3 * (x * abs(x))
Hessian Formula : (6 * x * x) / abs(x)
Value
The Cubic Error per value.
Laurae2/Laurae documentation built on May 8, 2019, 7:59 p.m.
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Description Usage Arguments Details Value
Description
This function computes the Mean Cubic Error loss (MCE) per value provided preds and labels.
Usage
1 | loss_MCE(y_pred, y_true)
|
Arguments
y_pred |
The |
y_true |
The |
Details
Supposing: x = preds - labels
Loss Formula : abs(x^3)
Gradient Formula : 3 * (x * abs(x))
Hessian Formula : (6 * x * x) / abs(x)
Value
The Cubic Error per value.
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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