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

Load the caret package.
Call confusionMatrix() on conf_matrix to print the accuracy of the model.
Review the output of confusionMatrix() and assign the accuracy of the model to accuracy.

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 <- ___