Supervised Learning — Classification, Regression, Generalizing, Overfitting, Underfitting

This article involves fundamental terms used in machine learning algorithms especially in supervised learning. The difference between regression and classification and other terms such as overfitting, underfitting, generalizing are explained with the examples clearly.

When it is modeled machine learning system basically, it is thought that dataset features as inputs, algorithm as a model (black box or gray box), and target of the features (the result of the inputs) as an output…