Machine Learning

Difference Between Classification and Regression in Machine Learning

Last Updated on May 22, 2019

There is an important difference between classification and regression problems.

Fundamentally, classification is about predicting a label and regression is about predicting a quantity.

I often see questions such as:

How do I calculate accuracy for my regression problem?

Questions like this are a symptom of not truly understanding the difference between classification and regression and what accuracy is trying to measure.

In this tutorial, you will discover the differences between classification and regression.

After completing this tutorial, you will know:

  • That predictive modeling is about the problem of learning a mapping function from inputs to outputs called function approximation.
  • That classification is the problem of predicting a discrete class label output for an example.
  • That regression is the problem of predicting a continuous quantity output for an example.

Let’s get started.

Difference Between Classification and Regression in Machine Learning

Difference Between Classification and Regression in Machine Learning
Photo by thomas wilson, some rights reserved.

Tutorial Overview

This tutorial is divided into 5 parts; they are:

  1. Function Approximation
  2. Classification
  3. Regression

    4. To finish reading, please visit source site