What is binary classification?

What is binary classification?

• A. A classification problem with two possible classes.
• B. A continuous prediction problem.
• C. A clustering task with many clusters.
• D. A regression task predicting a numeric value.

Answer: (A)

Binary classification is a supervised learning task where the goal is to assign each input to one of two possible categories. This means the model learns to differentiate between two labels, such as yes/no, spam/not spam, or disease present/absent. Even when the model outputs a probability for belonging to a class, a threshold is used to decide the final binary label, keeping it as two classes. This is distinct from other tasks: regression predicts a numeric value, and clustering groups data without predefined labels. So the statement that a binary classification problem has two possible classes is the correct description.

Binary classification is a supervised learning task where the goal is to assign each input to one of two possible categories. This means the model learns to differentiate between two labels, such as yes/no, spam/not spam, or disease present/absent. Even when the model outputs a probability for belonging to a class, a threshold is used to decide the final binary label, keeping it as two classes. This is distinct from other tasks: regression predicts a numeric value, and clustering groups data without predefined labels. So the statement that a binary classification problem has two possible classes is the correct description.