•Mixture of experts
–One expert per region
–Expert switching
•Bagging
–Multiple models on the complete
space, a learner is not biased to any region
–Learners are learned
independently
•Boosting
–Every learner covers the complete
space
–Learners are biased to regions
not predicted well by other learners
–Learners are dependent
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