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Each election year was predicted using only prior years.
Election prediction data science. The general election is coming up in november and prediction models based on polls and other factors have become a popular way of keeping track of its trajectory. Miller working paper revised 24 november 2020 abstract this paper reviews three election forecasting methods. The dataset was from the 2019 india general election.
Manuscript for research section volume 1 issue 1 january 2021 issn 2693 8871 print issn 2693 8863 online predicting the 2020 presidential election thomas w. Data science is just really a buzz word explained donald l. 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 presidential election is an event anticipated by us citizens and people around the world. What election prediction errors can teach us about data science. I recently competed in a kaggle competition where we have to predict the election results using mach i ne learning.
I selected the model and the features based on a time series cross validation scheme. The reason is that it. Comedian jon stewart once referred to him quite seriously as the god of the algorithm statistics were a game changer for politics.
Election prediction predicting the 2020 presidential general election. Using data science to predictwho will win the 2020 presidential election. As co editors of the special theme on elections for the harvard data science review we decided that it was important to incorporate both an academic and industry look at multiple aspects of the 2020 election from a high level discussion of different statistical and theoretical models by the most popular and well known pollsters to a study on how to estimate the magnitude of the lost votes.
Nate gained celebrity status through his accurate election predictions using statistical analyses. Others would take a different approach to where data science relates to polling. One based on data available as of september in the year prior to the election i e.
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