Feature Extraction
/ˈfiːtʃər ɪkˈstrækʃən/
The process of transforming raw data into numerical features that machine learning models can process.
Feature extraction identifies relevant information from data. In deep learning, this happens automatically through learned representations. Traditional ML requires manual feature engineering.
Examples
- Edge detection in images
- TF-IDF for text
- Convolutional features in CNNs