loss_Poisson: Laurae's Poisson Error (computation function)

In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R

Description

This function computes the Laurae's Poisson Error loss per value provided preds and labels count.

Usage

loss_Poisson(y_pred, y_true)

Arguments

y_pred	The predictions.
y_true	The labels.

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)

Value

The Laurae's Poisson Error per value.

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