Overview
Model-Based Learning
Creates a function F(x) using the given data to predict the output.
EX): Support Vector Machines
Instance-Based Learning
Uses the given data itself as the model. If an input is given, it will look through the current data and see which data is close to the input for prediction. No need for training, but it is difficult to generalize.
EX): KNN
