Random forest predictive model rendered using Shiny with interactive feature values and prediction
A random forest classifier built on the PimaIndiansDiabetes2 diabetes data set from the mlbench is trained and evaluated inside of a Shiny application. Inputs matching the data set are provided to allow the user to interactivel change the data and see the resulting prediction based on the trained model.