Decision Trees from large Databases: SLIQ

Bagging – Learning Robust Trees
• Bagging = Bootstrap aggregating
• Bagging – Algorithm:
Repeat k = 1 … M times :
Generate a sample dataset L k from L.
Compute model θ k for dataset L k .
• Combine the M learned predictive models:
Classification problems: Voting
Regression problems: Mean value
• Original reference:
L.Breiman: “Bagging Predictors”. 1996
e.g. a model tree
Sawade/Landwehr/Prasse/Scheffer, Maschinelles Lernen
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