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AdaBoost
AdaBoost
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AdaBoost trains a sequence of weak classifiers, each focused on the examples misclassified by previous ones. What is the core mechanism for shifting focus?
Hide and think first
A.
Each round increases the depth of the weak classifier, starting with stumps and progressing to full decision trees
B.
Each round adds more features to the input, focusing attention on features that correlate with errors
C.
Each round reweights training examples: misclassified ones get higher weight, correctly classified ones get lower weight
D.
Each round trains on a different random subset of the training data, with overlaps that emphasize harder examples
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