Toward Theory of Applied Learning. What is Machine Learning?

Various existing approaches to formalize machine learning (ML) problem are discussed. The concept of Intelligent Learning (IL) as a context of ML is introduced. IL is described following traditions of Hegel's logic. A general formalization of classification as Optimal Class Separation problem is proposed. The formalization includes two criteria, direct and proximity loss, introduced here. It is demonstrated that $k$-NN, Naive Bayes, decision trees, linear SVM solve Optimal Class Separation problem.