Creating ROC curves and ensembling models in R with "caret" | R Tutorial (2021)
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Part 1: • Preprocessing Data in R for ML with "caret...
Part 2: • Feature Elimination and Variable Importanc...
Part 3: • Training and Tuning ML Models in R with "c...
In this video I continue the tutorial series on machine learning in R to talk about the following topics: modifying boundaries for classifier thresholds, creating ROC curves, and ensembling the results of multiple models. We will supplement the "caret" package with "ROCR" and "caretEnsemble".
There are a few sources from which this tutorial draws influence and structure. The first is the GitHub documentation on "caret" from its creation, Max Kuhn. The second is a very well-written and comprehensive tutorial by author Selva Prabhakaran on Machine Learning Plus. Third is a helpful resource for dealing with class imbalance, as we often find with classification problems.
GitHub documentation from Max Kuhn: https://topepo.github.io/caret/
Tutorial by Selva Prabhakaran: https://www.machinelearningplus.com/m...