DataRobot Blog

This post looks into the problem of classification, a situation in which a response is a categorical variable. We will build upon the techniques that we previously discussed in the context of regression and show how they can be transferred to classification problems. This post introduces a number of classification techniques, and it will try to convey their corresponding strengths…

Earlier we covered Ordinary Least Squares regression with a single variable. In this posting we will build upon that by extending Linear Regression to multiple input variables giving rise to Multiple Regression, the workhorse of statistical learning. We first describe Multiple Regression in an intuitive way by moving from a straight line in a single predictor case to a 2d…

Linear regression, also called Ordinary Least-Squares (OLS) Regression, is probably the most commonly used technique in Statistical Learning. It is also the oldest, dating back to the eighteenth century and the work of Carl Friedrich Gauss and Adrien-Marie Legendre. It is also one of the easier and more intuitive techniques to understand, and it provides a good basis for learning…