Machine Learning Fundamentals
Cross-Validation
A technique for assessing model performance by partitioning data into subsets, training on some and validating on others.
Related Concepts
- K-Fold: Explore how K-Fold relates to Cross-Validation
- Validation: Explore how Validation relates to Cross-Validation
- Train-Test Split: Explore how Train-Test Split relates to Cross-Validation
- Model Evaluation: Explore how Model Evaluation relates to Cross-Validation
Why It Matters
Understanding Cross-Validation 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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machine-learning-fundamentals k-fold validation train-test-split