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1Nova Southeastern UniversityCollege of Engineering and ComputingMMIS 643 Data MiningSummer 2016(May 9 – August 14, 2016)Written Assignment #3Due Date: July 24, 2016Instructor: Dr. Junping SunA.A neural network typically starts out with random coefficients (weights); hence, it produce essentiallyrandom predications when presented with its first case. What is the key ingredients by which the net(neural network) evolves to produce a more accurate predication? (Please answer your question as clearlyand concisely as possible.) (10 points)B.Consider the Boston Housing Data file (The schema of the data file is given on page 33 in Table 2.2 ofthe textbook, the 3rdedition, page 27 of the 2ndedition. )(40 points)a.Study the Neural Networks Prediction example from the URL:http://www.solver.com/xlminer/help/neural-networks-classification-intro,and following the examplestep by step.b.Using XLMINER’s neural network routine to fit a model using XLMINER default values for neuralnetwork parameters by using the predictors such as CRIM, ZN, INDUS, CHAS, NOX, RM, AGE, DIS,RAD to classify the value ofCAT.MEDV.i.RecordtheRMSerrorsforthetrainingdataandthevalidationdata,andobservetheliftchartsfor repeating the process, changing the number of epochs to 300, 3000, 10,000, 20,000.ii.WhathappenstoRMSerrorforthetrainingdata set as the number of epochs increases?iii.WhathappenstoRMSerror for the validation data set as the number of epochs increases?iv.Commentsontheappropriatenumberofepochsforthemodel.Note:(PleaseusethePredictionOptionoftheNeuralNetworkinordertogetRMS)C.ForAssociationRuleMining,pleasedefinethefollowingterms:(10points)a.Supportb.Confidencec.LiftD.Study the Association Mining example from the URL:http://www.solver.com/xlminer/help/association-rules.

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