Model: This model has gathered data from nationwide Congressional elections from 2008, 2010, and 2012 along with voter registration data from 2008-2014, trends of each districts electorate in previous elections, and as each 2014 Primary Election is held, rolls that real time data into the assessment of candidates for Congress for the Fall 2014 elections. This model uses a Logic Regression Model and leverages predictive analysis of multiple data streams in determining the elections outcome of each district.
Initial Report - California: We generated an initial report on California data that showed Districts 25 and 33 are Statistically Unpredictable, where in the example of District 33, the Republican candidate received more votes in the June/2014 Primary, however given the Incumbent is a Democrat, the bias is toward an incumbent win. California District 33 can go either way, and thus special funding would be prudent by Campaign groups to sway the election their direction.
California District 25 has 2 Republicans vying for the Fall elections (California is one of only a handful of States where 2 members of the same party can run for final elections in the Fall, whereas most states, the Primary election selects 1 Republican and 1 Democrat to run against each other in the Fall). California District 25 has a unique challenge where the incumbent party has 2 candidates running against each other, but with VERY different political views and preferences (Tea Party Conservative vs Moderate Republican) that the House Leadership in Washington will need to determine whether a "win" by either of these individuals is preferred or not in the final outcome.
The model has so far successfully predicted the Primary elections for California, and as of the writing of this article, we have uploaded the data for nationwide districts that represent about 2/3 of the Congressional Seats that Primary elections have already been held.
And then ultimately the focus will be on the Fall General Elections and leveraging this information to do the best predictive job possible...
It has been a GREAT tool to work with in the early adopter program, and something that now that Azure ML is available to the general public as a Preview technology, this is something we will leverage for MANY other scenarios we've been using this for from healthcare, to banking, or insurance, to life sciences, to retail, to social media and more.
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