Us Election Result Prediction Using Machine Learning

This article explains how to clean and prepare the dataset create new features out of the existing ones and then predict the results using a popular machine learning algorithm.

Us election result prediction using machine learning. The primary objective of this paper is to model and forecast the united states presidential election via the usage of learning algorithms. He had previously predicted 2013 australian federal election and the 2015 queensland election with 95 per cent accuracy. A machine learning approach to predicting federal elections.

To test the performance of our model we divide the synthetic data into 10 folds train the model on 9 folds and examine its performance on the remaining one fold of data saved for testing. This study could be useful because it provides a reliable tool to make prediction on the vote result besides survey the voters. Predicting the 2016 us election results by county with supervised machine learning in r.

Mining interesting association rules that relate to demographics and voting preference in r. Elections is important for political scientists and political campaigns. Random forest is an ensemble supervised machine learning approach which our previous work has shown works well for detecting potential election fraud.

We carried out our analysis by comparing twitter results with traditional opinion polls. Despite most opinion polls and forecasts stating that hilary clinton would beat donald trump in the us presidential election the. Machine learning and shy voters they got it wrong again.

We devised an advanced classifier for sentiment analysis in order to increase the accuracy of twitter content analysis. I recently competed in a kaggle competition where we have to predict the election results using mach i ne learning. How to buy an election.

I have seen professor xue li predict the us correctly. It can potentially facilitate the electoral team and the media to understand di erent concerns from di erent states and the potential votes result. The location is needed so that the machine learning algorithm can make predictions for specific regions in the us.