What Does Hyperparameter Mean?

A hyperparameter is a machine learning parameter whose value is chosen before a learning algorithm is trained. Hyperparameters should not be confused with parameters. In machine learning, the label parameter is used to identify variables whose values are learned during training.


Every variable that an AI engineer or ML engineer chooses before model training begins can be referred to as a hyperparameter — as long as the value of the variable remains the same when training ends.

Examples of hyperparameters in machine learning include:

Techopedia Explains Hyperparameter

It’s important to choose the right hyperparameters before training begins because this type of variable has a direct impact on the performance of the resulting machine learning model.

The process of choosing which hyperparameters to use is called hyperparameter tuning. The process of tuning may also be referred to as hyperparameter optimization (HPO).

Margaret Rouse

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…