2019F-178-Mid

Bayes classifiers are probabilistic models based on Bayes' Theorem. They predict class membership by calculating the probability of a sample belonging to a class, assuming feature independence (as in Naive Bayes).

Mason Bennett
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CS178MidtermExamMachineLearningandDataMining:Fall2019MondayNovember4th,2019Yourname:Row/SeatNumber:YourID#(e.g.,123456789)UCINetID(e.g.ucinetid@uci.edu)«PleaseputyournameandIDoneverypage.«Totaltimeis50minutes.READTHEEXAMFIRSTandorganizeyourtime;don'tspendtoolongonanyoneproblem.«Pleasewriteclearlyandshowallyourwork.oIfyouneedclarificationonaproblem,pleaseraiseyourhandandwaitfortheinstructororTAtocomeover.Youmayuseonesheetcontaininghandwrittennotesforreference,anda(basic)calculator.Tuminyournotesandanyscratchpaperwithyourexam.Problems1BayesClassifiers,(10points.)32NearestNeighborRegression,(12points.)53Truo/False,(10points.)74SupportVectorMachines,(10points.)95VCDimensionality,(10points.)1Total,(52points.)

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