LogLoss: Log loss / Cross-Entropy Loss
In MLmetrics: Machine Learning Evaluation Metrics
View source: R/Classification.R
LogLoss R Documentation
Log loss / Cross-Entropy Loss
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)
MLmetrics documentation built on May 29, 2024, 9:34 a.m.
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View source: R/Classification.R
| LogLoss | R Documentation |
Log loss / Cross-Entropy Loss
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)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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