loss_MSE_xgb: Mean Squared Error (xgboost function)
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R
Description
Usage
Arguments
Details
Value
Description
This function computes for xgboost's obj function the Mean Squared Error loss (MSE) gradient and hessian per value provided preds and dtrain.
Usage
1
loss_MSE_xgb(preds, dtrain)
Arguments
preds
The predictions.
dtrain
The xgboost model.
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The gradient and the hessian of the Squared Error per value in a list.
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 for xgboost's obj function the Mean Squared Error loss (MSE) gradient and hessian per value provided preds and dtrain.
Usage
1 | loss_MSE_xgb(preds, dtrain)
|
Arguments
preds |
The |
dtrain |
The xgboost model. |
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The gradient and the hessian of the Squared Error per value in a list.
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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