zak100 Posted November 4, 2020 Share Posted November 4, 2020 Hi, I am trying to create a Byesian network to predict about the election results. For this election there are some important issues (I would call them as nodes) like EV, CD19, BLM, and WSM. I can assign some values to them. And then we can have two candidates, T and B, they belong to some party and these parties have workers. Now I have to arrange the nodes to indicate the dependencies and then assign conditional probabilities. Kindly guide me how can I improve my approach and what values should I assign to conditional probabilities and how to estbalish the network. Zulfi. Link to comment Share on other sites More sharing options...
PoetheProgrammer Posted November 4, 2020 Share Posted November 4, 2020 I’d break it down into individual states (you almost certainly need to regardless) and pull some polling data as a start to get probabilities. You’ll also need data about each states views on the issues at hand in order to properly account for them otherwise you’re just guessing. I would start with modeling an individual state (e.g. Texas) and building a backtester to verify results. Once you get that down add a couple of other states to guarantee you aren’t overfitting and scale up from there. 1 Link to comment Share on other sites More sharing options...
zak100 Posted November 4, 2020 Author Share Posted November 4, 2020 Hi, Thanks for your reply. <You’ll also need data about each states views on the issues at hand in order to properly account for them otherwise you’re just guessing. > I would search. Right now I have found general issues which I think are applicable to all states but of course there are issues like Economy, Climate Change, Migrants which can relate to other states. < I would start with modeling an individual state (e.g. Texas) and building a backtester to verify results.> This is what I wanted to do because I don't know how to create a network. Once I evaluate the results (wrong/right probabilities ) but with a correct nectwork, I think I can do that for other states. Please guide me how to establish dependencies and how to assume values for conditional probabilities table (CPT). Zulfi. Link to comment Share on other sites More sharing options...
zak100 Posted November 5, 2020 Author Share Posted November 5, 2020 Hi, I have created a bysian network using samiam tool. In the diagram, I have shown 3 major issues but let’s consider that there are 4 issues and I have got following data related to Texas state: C19=COVID19 = 38% EJ= Economy and Job (28%) R=Racism(9%) HC = Health care = (9%) Party Affiliations: D= Democrat = 39% Re =republican= 40% N = neutral There are total 17 million voters Somebody please guide me how can I use the above data to predict the inclination of voters to one of the two candidates in a two party System where one of the candidates is the incumbent (i.e. I want to get an estimate of the actual number of voters inclined towards a candiddate).Please feel free to suggest the modifications. Please guide Link to comment Share on other sites More sharing options...
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