Laurae (version 0.0.0.9001)

loss_MSE_xgb: Mean Squared Error (xgboost function)

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

loss_MSE_xgb(preds, dtrain)

Arguments

preds

The predictions.

dtrain

The xgboost model.

Value

The gradient and the hessian of the Squared Error per value in a list.

Details

Supposing: \(x = preds - labels\) Loss Formula : \(x^2\) Gradient Formula : \(2 * x\) Hessian Formula : \(2\)