Laurae (version 0.0.0.9001)

loss_MCE_xgb: Mean Cubic Error (xgboost function)

Description

This function computes for xgboost's obj function the Mean Cubic Error loss (MCE) gradient and hessian per value provided preds and dtrain.

Usage

loss_MCE_xgb(preds, dtrain)

Arguments

preds

The predictions.

dtrain

The xgboost model.

Value

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

Details

Supposing: \(x = preds - labels\) Loss Formula : \(abs(x^3)\) Gradient Formula : \(3 * (x * abs(x))\) Hessian Formula : \((6 * x * x) / abs(x)\)