LogLoss: Log loss / Cross-Entropy Loss

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

Description

Compute the log loss/cross-entropy loss.

Usage

LogLoss(y_pred, y_true)

Arguments

y_pred	Predicted probabilities vector, as returned by a classifier
y_true	Ground truth (correct) 0-1 labels vector

Value

Log loss/Cross-Entropy Loss

Examples

data(cars)
logreg <- glm(formula = vs ~ hp + wt,
              family = binomial(link = "logit"), data = mtcars)
LogLoss(y_pred = logreg$fitted.values, y_true = mtcars$vs)

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