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Computers and Technology, 21.04.2020 21:40 ameliaduxha7
Suppose you are running a learning experiment on a new algorithm for Boolean clas-sification. You have a data set consisting of 100 positive and 100 negative examples. You plan to use leave-one-out cross-validation and compare your algorithm to a baselinefunction, a simple majority classifier. (A majority classifier is given a set of training dataand then always outputs the class that is in the majority in the training set, regardlessof the input.) You expect the majority classifier to score about 50% on leave-one-outcross-validation, but to your surprise, it scores zero every time. Can you explain why?
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Suppose you are running a learning experiment on a new algorithm for Boolean clas-sification. You ha...
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