Laurae (version 0.0.0.9001)

loss_Poisson_math: Laurae's Poisson Error (math function)

Description

This function computes the Laurae's Poisson Error loss per value provided x, y (preds, labels) counts.

Usage

loss_Poisson_math(x, y)

Arguments

x

The predictions.

y

The labels.

Value

The Laurae's Poisson Error per value.

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 : \(y_true/(y_pred * y_pred)\)

Examples

## Not run: ------------------------------------
# SymbolicLoss(fc = loss_poisson_math, xmin = 1, xmax = 50, y = rep(10, 21))
## ---------------------------------------------