misclassification {xtune}

Calculate misclassification error

Description

misclassification calculate misclassification error between predicted class and true class

Usage

misclassification(pred, true)

Arguments

pred

Predicted class

true

Actual class

Value

Misclassification error for binary or multiclass outcome.

See Also

To calculate the Area Under the Curve (AUC) for binary or multiclass outcomes, please refer to the pROC.

Examples

Y1 <- rbinom(10,1,0.5)
Y2 <- rnorm(10,1,0.5)
misclassification(Y1,Y2)