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National Election Prediction
Lei Xu
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Motivation 2016 president election is coming.
Really useful for politicians who want to know which factors may determine a voter's choice. And I was fascinated by a TV series....
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Problem to Solve Given 4 characteristics of an individual voter,using artificial neural network to classify their voting choice. Data set contains 2000 individual-level turnout data. It pools several American National Election Surveys conducted during the 1992 presidential election year. 2,000 observations are included in the sample data.
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Data Set continue In the original data ,each table containing 5 variables ("race", "age", "educate", "income", and "vote"). 4 features: race educate income vote sample data race age educate income vote white 60 14 3.3458 1
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Approach Config the ANN sturture in MATLAB by modifiying Hesham Eraqi's code Sigmoid activation function Backpropagation training use mean square error(MSE) to messure the performance stops when MSE =0 or exceed the maximum epoch value
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Results MSE=0.020619 [10 10]; η:0.15; [10 10]; η:0.01; MSE=0
[10 10]; η:0.15; [10 10]; η:0.01; MSE=0 [10 10]; η:0.10 MSE=0
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[10 10]; η:0.15; MSE= [ ] η=0.15 MSE=0.1856 [5 5] η=0.15 MSE=
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Discussion The simpler the better job, but not always.
The learning rate η doesn't impact the performance too much using the ANN to analyze the whole country voter data ,we may predict the final result of the election. limitation Future development
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Reference King, Gary, Michael Tomz, Jason Wittenberg (2000). “Making the Most of Statistical Analyses: Improving Interpretation and Presentation,” American Journal of Political Science, vol. 44, pp.341–355. Lecture Slides
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Thanks
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