Feature Engineering for Election Results Prediction Using Machine Learning
Sonali Mahendrakar
Machine Learning, Feature Engineering,Data preprocessing,Supervised Learning
In this present generation where political landscape as in political parties based on election commissions for the respective countries has always been complex in nature as it involves not only the elector’s opinion but also the general public opinion from which the ruling party will be decided. Several studies have shown how public opinion matters in analyzing various decisions such as in the case of political elections. This has been done by analyzing and working on numerous social media networking platforms and websites. The consistent rise of social media has given people the opportunities to openly discuss and debate various issues and consequences happening around the world there by considering issues such as political elections predictions, weather analysis and its prediction, credit card fraud prediction and many more. All these prediction cases can be generally be calculated by implementing them by using various technologies such as machine learning,data science etc. In this following project which deals with the technology machine learning it predicts the chances of winning political party in the upcoming elections .This has been predicted by using machine learning algorithms which also derive the accuracy for the given dataset used. The dataset has been collected from twitter social media platform where general public that is citizens of that particular country can openly participate, which is based on citizens of that specific country which is dependent on elections and political campaigns.Based on this scenario we have generated a machine learning model based on data preprocessing.
Article Details
Unique Paper ID: 155644

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 1248 - 1251
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