Review:
Decision Tree Algorithm
overall review score: 4.5
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score is between 0 and 5
A decision tree algorithm is a popular machine learning technique used for classification and regression tasks. It builds a model using a tree-like structure of decisions based on features and splits the data into branches to make predictions.
Key Features
- Simple to understand and interpret
- Can handle both numerical and categorical data
- Does not require extensive data preprocessing
- Capable of handling missing values
Pros
- Easy to visualize and explain to non-experts
- Works well with large datasets
- Handles irrelevant attributes well
Cons
- Prone to overfitting if not properly pruned
- Sensitive to noisy data