3 Types of Classification Problems in Machine Learning

Deep dive analysis of Binary Classification, Multi-class classification, and Multi-label classification

(Image by Author)

Classification in machine learning refers to a supervised approach of learning target class function that maps each attribute set to one of the predefined class labels. In other words, classification refers to predictive modeling where a target class is predicted given a set of input data.

There are various types of Classification problems, such as:

1. Binary Classification
2. Multi-class Classification
3. Multi-label Classification

In the further article, you can read about a deep-dive understanding of the above-mentioned classification types along with their evaluation metrics and examples.

1. Binary Classification:

Binary Classification is a type of supervised classification problem where the target class label has two classes and the task is to predict one of the classes. Typically, the task involves one class in a normal state and another class in an abnormal state.