Systems and methods for predicting whether experimental legislation will become enacted into law

At least one non-transitory computer readable medium containing processor readable code for programming one or more processors to perform a method comprising:

• transmitting from a user a first request which generates test content as an experimental law, the experimental law proposing language directed to a not-yet-drafted bill;
• transmitting from the user a second request pertaining to a selection by the user of an amount of potential sponsors of the not-yet-drafted bill;
• importing automatically over a network, data from the plurality of databases;
• preparing the data as a plurality of predictive modeling data;
• splitting the plurality of predictive modeling data into two sets of data, comprising a set of training data and a set of test data;
• training a two-class neural network on the training data to evaluate a predictive performance of the not-yet-drafted bill;
• generating a set of results from the training data;
• cross-validating the set of results with the test data;
• and
• deploying, over the network, a predictive performance, wherein the predictive performance is viewable on a network browser.

A non-transitory computer readable medium storing instructions executable by at least one processing device, the instructions including instructions to:

• transmit from a user a first request which generates test content as an experimental law, the experimental law proposing language directed to a not-yet-drafted bill;
• transmit from the user a second request pertaining to a selection by the user of an amount of potential sponsors of the not-yet-drafted bill;
• automatically import, over a network, data from the plurality of databases;
• prepare the data as a plurality of predictive modeling data;
• split the plurality of predictive modeling data into two sets of data, comprising a set of training data and a set of test data;
• train a two-class neural network on the training data to evaluate a predictive performance of the not-yet-drafted bill;
• generate a set of results from the training data;
• cross-validate the set of results with the test data;
• and
• deploy, over the network, a predictive performance, wherein the predictive performance is viewable on a network browser.