Accuracy of your model
Accuracy of the model can be calculated as:
$$\text{Accuracy} = \frac{\text{ TP + TN }}{\text{ TP + TN + FP + FN }}$$
where
- True negatives (TN): You correctly identified active employees
- True positives (TP): You correctly identified inactive employees
- False positives (FP): You predicted employees as inactive, but they are actually active
- False negatives (FN): You predicted employees as active, but they are actually inactive
confusionMatrix()
function from caret
package automatically calculates the accuracy of the model along with other relevant statistics.
This exercise is part of the course
HR Analytics: Predicting Employee Churn in R
Exercise instructions
- Load the
caret
package. - Call
confusionMatrix()
onconf_matrix
to print the accuracy of the model. - Review the output of
confusionMatrix()
and assign the accuracy of the model toaccuracy
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load caret
library(___)
# Call confusionMatrix
___
# Choose the model's accuracy as per confusionMatrix output (0.9283 or 92.83)?
accuracy <- ___