Intermediate · Data
Feature spec
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A feature spec defines how to extract and interpret features from data, specifying their type and shape for model consumption.
Technical Definition
A feature spec defines how to extract and interpret features from data, specifying their type and shape for model consumption.
How it works
A feature specification, often used in frameworks like TensorFlow, describes the necessary information to parse features from raw data, such as tf.Example protocol buffers. It includes details like the feature name, data type (e.g., integer, float), and shape (e.g., fixed or variable length). This ensures that the model correctly understands and uses the input features.
Related Concepts
- Feature Engineering — The process of creating, selecting, and transforming input variables to improve a machine learning model's performance.