What are the major differences among the three methods for
increasing the accuracy of a classifier:
(a)...
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What are the major differences among the three methods forincreasing the accuracy of a classifier:
(a) bagging,
(b) boosting, and
(c) ensemble?
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Bagging otherwise known as bootstrap aggregating is used to reduce variance which helps avoid overfitting The idea is that once you have your sample from bootstrapping you can then build a series
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