Machine Learning with Caret in R: Part 2- Complete Analysis (Classification)

This video walks through the process of carrying out a complete machine learning analysis from data partition, setting up k-fold cross-validation resampling to tune hyperparameters, evaluating the fit on the holdout (test) set and then using the final model for scoring new data.

00:00 Introduction
00:54 Initial Setup
01:55 Setup trainControl
02:34 Model specification- Enet, Random Forest and Stochastic Gradient Boosting
03:54 Hyper-parameter Tuning
04:53 Training various models
09:44 Obtaining the best model from each algorithm
11:21 Performance evaluation on test set
17:17 Obtaining multiple lift and ROC cruves
19:05 Deploying the final model