Review:
Decision Trees
overall review score: 4.5
⭐⭐⭐⭐⭐
score is between 0 and 5
Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are tree-like structures where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome or prediction.
Key Features
- Used in both classification and regression tasks
- Easy to interpret and visualize
- Can handle both numerical and categorical data
- Non-parametric method
Pros
- Easy to understand and interpret
- Can handle both numerical and categorical data
- Non-parametric method allows for flexibility in modeling complex relationships
Cons
- Tends to overfit with high variance if not pruned properly
- Sensitive to noisy data