loss_MCE_xgb: Mean Cubic Error (xgboost function)
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R

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

1	loss_MCE_xgb(preds, dtrain)

`preds`	The `predictions`.
`dtrain`	The xgboost model.

Supposing: x = preds - labels

Loss Formula : abs(x^3)

Gradient Formula : 3 * (x * abs(x))

Hessian Formula : (6 * x * x) / abs(x)

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

Laurae2/Laurae documentation built on May 8, 2019, 7:59 p.m.

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