Decision Tree Learning

• Decision Tree Learning
• Decision Tree
• Learned Rules
• When to use Decision Tree Learning
• ID3 Algorithm
• What Attribute is the Best Classifier?
• Information Gain
• Information Gain Example
• Decision Tree Example
• Partially Grown Tree
• Final Tree
• Searching in Decision Trees
• ID3 Hypothesis Space
• Inductive Bias in Decision Tree Learning
• Restriction Biases and Preference Biases
• Occam's razor
• Avoiding Overfitting
• Overfitting in Decision Trees
• Approaches to Overfitting
• Reduced Error Pruning
• Impact of Reduced Error Pruning
• Rule Post Pruning
• Improved Estimated Accuracy
• Why convert to rules?
• Continuous Valued Attributes?
• Example
• Other Measures for Picking Attributes
• Problems with Gain Ratio
• Missing Attribute Values in Train. Ex.
• Attributes with Differing Costs
• Summary
• Summary continued