Feature Selection
Choosing the most relevant features from available data to reduce dimensionality and improve model performance.
Related Concepts
- Feature Engineering: Explore how Feature Engineering relates to Feature Selection
- Dimensionality Reduction: Explore how Dimensionality Reduction relates to Feature Selection
- Feature Importance: Explore how Feature Importance relates to Feature Selection
Why It Matters
Understanding Feature Selection is crucial for anyone working with machine learning fundamentals. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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Related Terms
Dimensionality Reduction
Techniques to reduce the number of input features while preserving important information (PCA, t-SNE, autoencoders).
Feature Engineering
The process of selecting, transforming, and creating input features to improve model performance.
Feature Importance
Measures indicating which features contribute most to model predictions, useful for interpretation and selection.