# logloss

It measures the performance of a classification model where the output of the classification model is in terms of probability. It takes into account the uncertainty of the predictions based on how much it varies from the actual label. Best Value: 0 Worst Value: tends to infinity (it increases as the predicted probability value diverges from actual label).

## Syntax

Loss = logloss(targets,predictions)

## Inputs

targets
Actual label for each observation.
Type: double
Dimension: vector
predictions
Predicted value for each observation.
Type: double
Dimension: vector

## Outputs

Loss
Log loss of the classifier.
Type: double
Dimension: scalar

## Example

Usage of logloss

targets = [1, 0];
predictions = [0, 1];
score = logloss(targets, predictions);
> score
score = 24.1771435