Decision Tree
A tree-structured model that makes decisions by splitting data based on feature values, interpretable but prone to overfitting.
Related Concepts
- Random Forest: Explore how Random Forest relates to Decision Tree
- Classification: Explore how Classification relates to Decision Tree
- Regression: Explore how Regression relates to Decision Tree
- Tree-based Methods: Explore how Tree-based Methods relates to Decision Tree
Why It Matters
Understanding Decision Tree 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
Classification
A supervised learning task where the model predicts discrete class labels (categories) for input data.
Random Forest
An ensemble of decision trees trained on random subsets of data and features, reducing overfitting through averaging.
Regression
A supervised learning task where the model predicts continuous numerical values rather than discrete categories.