1. National Election Prediction
Lei Xu

2. 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....

3. 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.

4. 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

5. 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

6. 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

7. [10 10]; η:0.15;
MSE=
[ ] η=0.15
MSE=0.1856
[5 5] η=0.15
MSE=

8. 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

9. 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

10. Thanks