Poisson_LogLoss: Poisson Log loss

In LqNoob/Machine-Learning-Evaluation-Metrics: Machine Learning Evaluation Metrics

Description

Compute the log loss/cross-entropy loss.

Usage

Poisson_LogLoss(y_pred, y_true)

Arguments

y_pred	Predicted labels vector, as returned by a model
y_true	Ground truth (correct) labels vector

Value

Log loss/Cross-Entropy Loss

Examples

d_AD <- data.frame(treatment = gl(3,3), outcome = gl(3,1,9),
                   counts = c(18,17,15,20,10,20,25,13,12))
glm_poisson <- glm(counts ~ outcome + treatment,
                   family = poisson(link = "log"), data = d_AD)
Poisson_LogLoss(y_pred = glm_poisson$fitted.values, y_true = d_AD$counts)

LqNoob/Machine-Learning-Evaluation-Metrics documentation built on May 20, 2019, 3:33 p.m.