Problem: (20 Marks) The following data are recorded from an experiment to determine if the weight of an animal can be predicted after a given period of time on the basis of the initial weight of the...

Problem: (20 Marks) The following data are recorded from an experiment to determine if the weight of an animal can be predicted after a given period of time on the basis of the initial weight of the animal and the amount of feed that was eaten. Final Weight (y) Initial Weight (x1): Feed Weight (x2): 95 42 272 77 33 226 80 33 259 100 45 292 97 39 311 70 36 183 50 32 173 80 41 236 92 40 230 84 38 235 A multiple linear regression (MLR) model is fitted and the a few results of the analysis are shown below: Results of Multiple Regression SST = 2020.5 SSE = 256.284 SSR = 1764.216 R 2 = SSR/SST=0.873
Answer the following: (a) Use a neural network with 3 hidden inputs and present your results including the network diagram. (b) Compare your ANN results with the results of MLR method. (c) Does ANN give better forecasting than MLR? Give the reasons in details to support your conclusion.


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Assignment 2 ST403 Due Date: October 15, 2016 (Week 14) Mark = 20 Weight = 5% Problem: (20 Marks) The following data are recorded from an experiment to determine if the weight of an animal can be predicted after a given period of time on the basis of the initial weight of the animal and the amount of feed that was eaten. Final Weight (y) Initial Weight (x1): Feed Weight (x2): 95 42 272 77 33 226 80 33 259 100 45 292 97 39 311 70 36 183 50 32 173 80 41 236 92 40 230 84 38 235 A multiple linear regression (MLR) model is fitted and the a few results of the analysis are shown below: Results of Multiple Regression SST = 2020.5 SSE = 256.284 SSR = 1764.216 2 R = SSR/SST=0.873 Answer the following: (a) Use a neural network with 3 hidden inputs and present you results including the network diagram. (b) Compare your ANN results with the results of MLR method. (c) Does ANN give better forecasting than MLR? Give the reasons in details to support your conclusion.



May 13, 2022
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