Glossary

Feature Selection in machine learning involves choosing the most significant input variables or features for model construction, enhancing accuracy and efficiency.

Feature Extraction is a crucial data preparation step in machine learning. It entails altering raw data into a digestible format by choosing, filtering, and lowering data dimensions. It aids in identifying relevant features instrumental to effectively train machine learning models.

Fast-And-Frugal Trees are decision-making models using a simple structure for categorizing objects or making decisions. They quickly execute tasks while minimizing the usage of information.