ブースティング
1. BoostingBoosting is a machine learning meta-algorithm for performing supervised learning. Boosting is based on the question posed by Kearns: can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification (it can label examples better than random guessing). In contrast, a strong learner is a classifier that is arbitrarily well-correlated with the true classification.
Read “Boosting” on English Wikipedia
Read “ブースティング” on Japanese Wikipedia
Read “Boosting” on DBpedia
Read “Boosting” on English Wikipedia
Read “ブースティング” on Japanese Wikipedia
Read “Boosting” on DBpedia
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