Review:
Decision Tree
overall review score: 4.5
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score is between 0 and 5
A decision tree is a flowchart-like structure in which each internal node represents a 'test' on an attribute, each branch represents the outcome of the test, and each leaf node represents a class label.
Key Features
- Tree-like structure
- Nodes representing tests on attributes
- Branches representing outcomes of tests
- Leaf nodes representing class labels
Pros
- Easy to understand and interpret
- Can handle both numerical and categorical data
- Does not require data normalization
- Can handle multi-output problems
Cons
- Prone to overfitting if not properly pruned
- Sensitive to noisy data