In this video, I cover the concepts and practical aspects of building a classification model using the R programming language; starting from loading in the iris dataset, splitting the dataset, building the training model and cross-validation models using support vector machine, evaluating the prediction performance as well as the feature importance.
0:39 Download code from Data Professor GitHub
5:28 Practice: Make scatter plot comparing Training and Testing sets (distribution)
7:35 Mean centering
11:16 Building Training and CV models in R
15:38 Model performance metrics
16:54 Feature importance