A machine learning technique that uses evolutionary algorithms to select the most relevant features for a model, optimizing performance by removing redundant or irrelevant data, thus improving accuracy and reducing computation time.

• Natural Language Processing
• Computer Vision
• Recommendation Systems
• Time Series Analysis
• Bioinformatics

Consider a supervised learning task where a model is trained on a dataset with 100 features, but only 50 of them are actually relevant for the task. Evolutionary Feature Selection can be used to identify these irrelevant features and remove them from the dataset, resulting in a more accurate and efficient model.

• Semantic Data Model – Introduction