Glossary

What is Model Output?

Model Output definition
February 3, 2025
Model Risk Management

Model output is the prediction or decision made by a machine learning model based on input data.

In supervised learning, the model output is a predicted target value for a given input. In unsupervised learning, the model output may include cluster assignments or other learned patterns in the data.

Model output can be a single value, a probability distribution, a class label, or a series of continuous or discrete values, and is often used to evaluate the performance of a machine learning model.

About the

Author(s)

Yields logo
Yields

Behind Yields is a team of experts in risk, regulation, and technology. When we write as Yields, we share our combined knowledge to make complex topics clear and actionable.

Yields Model Risk Management (MRM) Suite

Staying compliant with evolving regulations, especially across different countries, is challenging. The Yields MRM Suite provides advanced tools specifically designed to help with Model Risk Management regulations, ensuring you meet these specific requirements effectively.

Related Articles

Glossary

What is Model Validation Frequency?

Read more
What is Model Validation Frequency?
E-book

Navigating SR 26-2: New technological requirements for model risk management

Read more
Navigating SR 26-2: New technological requirements for model risk management
Article

Comprehensive Overview of US Banking Laws and Regulations

Read more
Comprehensive Overview of US Banking Laws and Regulations
No items found.