Classification is one of the major problems that we solve while working on standard business problems across industries. In this article we'll be discussing the major three of the many techniques used for the same, Logistic Regression, Decision Trees and Support Vector Machines [SVM]. All of the above listed algorithms are used in classification [ SVM and Decision Trees are also used for regression, but we are not discussing that today!]. Time and again I have seen people asking which one to choose for their particular problem. Classical and the most correct but least satisfying response to that question is "it depends!".

Classification is one of the major problems that we solve while working on standard business problems across industries. In this article we'll be discussing the major three of the many techniques used for the same, Logistic Regression, Decision Trees and Support Vector Machines [SVM]. All of the above listed algorithms are used in classification [ SVM and Decision Trees are also used for regression, but we are not discussing that today!]. Time and again I have seen people asking which one to choose for their particular problem. Classical and the most correct but least satisfying response to that question is "it depends!".

This is the 2nd part of the series. In this part we'll discuss how to choose between Logistic Regression, Decision Trees and Support Vector Machines. The most correct answer as mentioned in the first part of this 2 part article, still remains it depends. We'll continue our effort to shed some light on, it depends on what. All three of these techniques have certain properties inherent by their design, we'll elaborate on some in order to provide you with few pointers on their selection for your particular business problem.