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Data analytics to predict the income and economic hierarchy on Census data

机译:数据分析可预测人口普查数据的收入和经济等级

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摘要

The US Census Bureau conducts the American Community Survey generating a massive dataset with millions of data points. The rich dataset contains detailed information of approximately 3.5 million households in regard to who they are and how they live including ancestry, education, work, transportation, internet use and so on. This enormous data encourages the need to know more about the population and to derive insights. The ever demanding requirement in exposing the subtlety in case of economic issues is the motivation behind to construe meaningful conclusions in income domain. Hence the focus is to concentrate on bringing out unique insights into the financial status of the people living in the country. These conclusions delineated might aid in delivering wiser decisions in regard to economic growth of the country. Using relevant attributes, demographic graphs are plotted aiding the conclusions drawn. Also classifications into various economic classes are done using well known classifiers.
机译:美国人口普查局进行了美国社区调查,生成了包含数百万个数据点的海量数据集。丰富的数据集包含大约350万个家庭的详细信息,包括他们的身份以及他们的生活方式,包括血统,教育,工作,交通,互联网使用等。如此庞大的数据促使人们需要了解更多有关人口的知识并获得见解。揭露经济问题中的微妙之处的迫切要求是在收入领域解释有意义的结论的动机。因此,重点是集中于对居住在该国的人们的财务状况提出独特的见解。这些结论可能有助于做出有关该国经济增长的明智决定。使用相关属性,可以绘制人口统计图,以帮助得出结论。还使用众所周知的分类器将其分类为各种经济类别。

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