通过使用数据挖掘和机器学习分析一个普通人的政治偏好

G. Gokulkumari, M. Ravichand, Pooja Nagpal, Renu Vij
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引用次数: 0

摘要

使用学习算法和博弈论,提供一个估计给定投票人口可能的政治倾向的程序。在线和现场投票的结合是我们战略的第一步。由于选民对政治候选人的偏好是通过品质的线性等级来表达的,零和博弈策略可能会公平地分配选票总数。在2020年9月我市举行的少校选举的案例研究中,我们将我们的方法用于选举前景。研究结果很有希望。我建议在正品营销活动中使用这种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyze the political preference of a common man by using data mining and machine learning
Using learning algorithms and game theory, provide a procedure for estimating the likely political leanings of a given voting population. A combination of online and in-person polling was the first step in our strategy. With voters’ preferences for political candidates expressed via a linear hierarchy of qualities, a zero-sum game strategy may divide the total number of votes fairly. In a case study of the Major’s election in our city, which took place in September 2020, we put our approach to work for electoral prospection. The findings were quite promising. I suggest using this method in marketing campaigns for genuine products.
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