loss_MSE: Mean Squared 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 Squared Error loss (MSE) per value provided preds and labels.
Usage
1
loss_MSE(y_pred, y_true)
Arguments
y_pred
The predictions.
y_true
The labels.
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The Squared Error per value.
Laurae2/Laurae documentation built on May 8, 2019, 7:59 p.m.
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.
Description Usage Arguments Details Value
Description
This function computes the Mean Squared Error loss (MSE) per value provided preds and labels.
Usage
1 | loss_MSE(y_pred, y_true)
|
Arguments
y_pred |
The |
y_true |
The |
Details
Supposing: x = preds - labels
Loss Formula : x^2
Gradient Formula : 2 * x
Hessian Formula : 2
Value
The Squared 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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.