Machine Learning
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AdaBoost
Quick Definition
Combining weak classifiers with adaptive sample weighting
Full Definition
Adaptive Boosting, an ensemble algorithm combining weak classifiers by assigning higher weights to misclassified samples.
Examples
face detection, binary classification, sequential ensemble
Related Terms
boosting
ensemble-learning
decision-tree
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