Feature

How it is used

You add, create, select or drop features, and analysts ask which features are most important. Statisticians may say 'predictor', 'independent variable' or 'covariate' for the same idea.

Example sentences

1. Adding a 'days since last purchase' feature improved the model a lot.

2. Which features does the model rely on most?

Common collocations

• add a feature
• feature importance
• feature selection
• input feature

Related terms

• feature engineeringThe work of creating new input variables from raw data to help a model learn, for example turning a date of birth into an age or counting a customer's purchases.
• modelA mathematical representation of a real process, built from data, that is used to explain relationships or to make predictions about new cases.
• variableA characteristic that can take different values from one case to another, such as age, city or price; in a table it is usually one column.
• target variableThe value a model is trained to predict, such as whether a customer will churn or how much they will spend; also called the label or dependent variable.

This word in other fields

The same English word can have a different meaning in another field:

• feature · Software Engineering
• feature · Artificial Intelligence & Machine Learning
• feature · Product Management
• feature · Journalism & Media

More terms: Modelling and Machine Learning

• training data
• overfitting
• regression
• classification
• accuracy
• precision
• recall
• cross-validation
• baseline
• test set
• clustering