4 Types of Classification Tasks in Machine Learning

Last Updated on August 19, 2020

Machine learning is a field of study and is concerned with algorithms that learn from examples.

Classification is a task that requires the use of machine learning algorithms that learn how to assign a class label to examples from the problem domain. An easy to understand example is classifying emails as “spam” or “not spam.”

There are many different types of classification tasks that you may encounter in machine learning and specialized approaches to modeling that may be used for each.

In this tutorial, you will discover different types of classification predictive modeling in machine learning.

After completing this tutorial, you will know:

• Classification predictive modeling involves assigning a class label to input examples.
• Binary classification refers to predicting one of two classes and multi-class classification involves predicting one of more than two classes.
• Multi-label classification involves predicting one or more classes for each example and imbalanced classification refers to classification tasks where the distribution of examples across the classes is not equal.

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