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The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on …
The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training and tuning across a wide variety of modeling techniques. It also includes methods for pre-processing training data, calculating variable importance, and model visualizations.
An example from classification of music genres is used to illustrate the functionality on a real data set and to benchmark the benefits of parallel processing with several types of models.
Bio: Max is a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He has been applying models in the molecular diagnostic and pharmaceutical industries for over 15 years. He is the author of several R packages including the caret package that provides a simple and consistent interface to over 100 predictive models available in R.
Max has taught courses on modeling within Pfizer and externally. Recently, he taught modeling classes for the American Society of Chemistry, the Indian Ministry of Information Technology and Predictive Analytics World. He is a co-author of the forthcoming Spring book "Applied Predictive Modeling".