[Machine Learning]--Improving classification with the AdaBoost meta-algorithm
2016-08-06 16:45
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Let’ s see some basic Concepts!
Boosting Algorithm_wiki: is a machine learning ensemble(means all) meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms which convert weak learners to strong ones.
meta-algorithm: is just an informal, qualitative term, meaning an algorithm that exists to manipulate some other algorithms, which can can take the form of using different algorithms, using the same algorithm with different settings, or assigning different parts of the dataset to different classifiers.
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Boosting Algorithm_wiki: is a machine learning ensemble(means all) meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms which convert weak learners to strong ones.
meta-algorithm: is just an informal, qualitative term, meaning an algorithm that exists to manipulate some other algorithms, which can can take the form of using different algorithms, using the same algorithm with different settings, or assigning different parts of the dataset to different classifiers.
An Awesome Article to Summarize These Confusing Concepts( bootstrap, boosting, bagging )
Click Me
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