loss_Poisson_xgb: Laurae's Poisson Error (xgboost function)
Description
This function computes for xgboost's obj function the Laurae's Poisson Error loss gradient and hessian per value provided preds and dtrain. Negative and null values are set to 1e-15.Usage
loss_Poisson_xgb(preds, dtrain)
Value
The gradient and the hessian of the Laurae's Poisson Error per value in a list.Details
This loss function is strictly positive, therefore defined in \]0, +Inf\[. It penalizes lower values more heavily, and as such is a good fit for typical problems requiring fine tuning when undercommitting on the predictions. The negative values are cancelled out to make the loss function positive, with loss = 0 when y_true = y_pred. This loss function is experimental. Loss Formula : \((y_pred - y_true * log(y_pred))\) Gradient Formula : \(1 - y_true/y_pred\) Hessian Formula : \(y_true/(y_pred * y_pred)\)