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Exam2_sols_pg3 - 3 A dataset has 5 attributes{A1 A2 A A4 A...

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Unformatted text preview: 3. A dataset has 5 attributes {A1, A2, A, A4, A,} which are to be used to classify a sixth attribute called “class” There are three possible values of class { C1; C2, C3}. Define the architecture for a backpropagation neural network you could use to build a classification model for the data, Be sure to specify the number of nodes in each level as well as the activation function you would use at each node. [10 pts.] Acrlvfi'flafl l—U’VCf/alo g +1 me‘w - Swear-5 +2 0 Urfiaf —— twee/2 llowing questions. The matrix comes from a 4. Use the confusion matrix shown below to answer the fa [20 pts] set of test cases evaluated by a neural network Desired Classification 1 2 3 1 48 y 3 1 Network 2 4 25 20 ' Classification 3 22 30 Unknown 2 V my 5;“ a 57:; a.) What is the percentage of correct classifications produced by this network? Show work +3.5 30’ _ M‘- Xiae "e‘g éé,9% 514+ 5'6 +- 5.9 b‘) On which classification(s) does the network perform the best? Acme.“ C1 49/59” = ,9; . —-d1 c 1 ivy/n = 5a 94 “- H T“? 5937* e 7 3a/ so : 699/0 Aware/99f c) What can you say about the unknown classifications? 7:9; W966 oufpwvgr' 6F 7—,“; mp Arse AMT Sit-‘uiFJé‘afiaafLX D/F/rerzso-r gwusu Fara awe of: “nine genera?” ,aoms“ 75 155. pew {wasp a? W/zvv 5/? d) What type of hybrid classification structure might you try to improve the classification accuracy of the data being modeled? 1116711101611: 5; Pfififi-r?§ {fl-A as i, Fm»:- 77a 5 eta-roe Hflyé 0:95 We. §V€E2f7r£fm5 Mgr ” 6‘ng ,9 5-} #6 7mg 61?}: (Ml 4;; 3. fgyfisfii/fi'ffip #37? :flé.fiflfi J— /5 gym?" 7'64 whim/u ,Ffrqzwgfi'xfirfié' Céfiss o7 F/‘FcM c3404 ExamfiZDSC-O40604doc —- 3 ...
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