Measure final model performance

Now its time to calculate the test performance of your final model (logistic regression). Here you will use the held out testing data to characterize the performance you would expect from this model when it is applied to new data.

This exercise is part of the course

Machine Learning in the Tidyverse

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Exercise instructions

Use table() to compare the test_actual and test_predicted vectors.
Calculate the test accuracy.
Calculate the test precision.
Calculate the test recall.
After this exercise, you are done with the course! If you enjoyed the material, feel free to send Dmitriy a thank you via Twitter. He'll appreciate it. Tweet to Dmitriy

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Compare the actual & predicted performance visually using a table
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# Calculate the test accuracy
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# Calculate the test precision
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# Calculate the test recall
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Edit and Run Code