Examples

1. 1.

   For example, the following two machine learning models each perform binary classification:

2. 2.

   A model that determines whether email messages are spam (the positive class) or not spam (the negative class).

3. 3.

   A model that evaluates medical symptoms to determine whether a person has a particular disease (the positive class) or doesn't have that disease (the negative class).

Real-world uses

Created for this library

1. 1.

   A subscription business frames churn as a binary classification problem with labels churned and retained over a 30-day window.

2. 2.

   A bank uses binary classification to predict whether a transaction is fraudulent or legitimate at authorization time.

3. 3.

   A radiology startup builds a binary classifier to label chest X-rays as pneumonia or non-pneumonia for triage in the emergency department.