Disadvantages of Decision Trees
- Overfitting: Decision trees can easily overfit the training data, especially if they are deep with many nodes.
- Instability: Small variations in the data can result in a completely different tree being generated.
- Bias towards Features with More Levels: Features with more levels can dominate the tree structure.
Decision Tree
Decision trees are a popular and powerful tool used in various fields such as machine learning, data mining, and statistics. They provide a clear and intuitive way to make decisions based on data by modeling the relationships between different variables. This article is all about what decision trees are, how they work, their advantages and disadvantages, and their applications.
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