How To Estimate Model Accuracy in R Using The Caret Package

Last Updated on August 15, 2020

When you are building a predictive model, you need a way to evaluate the capability of the model on unseen data.

This is typically done by estimating accuracy using data that was not used to train the model such as a test set, or using cross validation. The caret package in R provides a number of methods to estimate the accuracy of a machines learning algorithm.

In this post you discover 5 approaches for estimating model performance on unseen data. You will also have access to recipes in R using the caret package for each method, that you can copy and paste into your own project, right now.

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Estimating Model Accuracy

We have considered model accuracy before in the configuration of test options in a test
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