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Decision Trees and Occam by Sumana Basu is a document available to read on EtoBox.
What is Decision Trees and Occam about?
The document discusses decision tree learning and some key concepts: - Decision trees are a widely used method for inductive inference that can approximate discrete-valued functions. They represent learned functions as tree structures. - The ID3 algorithm builds decision trees in a top-down manner by selecting the attribute that best splits the training examples at each step, based on information gain. - Overfitting can occur if trees are allowed to grow too deep. Strategies like reduced-error pruning p
- Author
- Sumana Basu
- Language
- EN