Beginner · Fundamentals
Feature set
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A feature set is the collection of all input features used by a machine learning model during training and inference.
Technical Definition
A feature set is the collection of all input features used by a machine learning model during training and inference.
How it works
A feature set comprises all the variables or attributes selected for a machine learning model to learn from. These features are the basis upon which the model makes predictions. The quality and relevance of the feature set are critical for the model's overall performance and accuracy.
Related Concepts
- Feature Engineering — The process of creating, selecting, and transforming input variables to improve a machine learning model's performance.
- Data Preprocessing — Transforming raw data into a format suitable for model training.
- Feature vector — A feature vector is a numerical representation of an example, composed of its feature values, used as input for machine learning models.