Figure 4.

A typical supervised learning workflow. (a) Exploratory data analysis is followed by a feature extraction step to derive putative discriminatory variables. The observations are split into training and testing data sets, and the predictive model trains on the training data set. Training involves the SVM model generalization step. Finally, the model’s generalization performance computes using the testing dataset. (b) Real-time classification workflow. SVM real-time classification using a predictive model.