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

机译:数据分析预测人口普查数据的收入和经济层次结构

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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:美国人口普查局通过数百万数据点来开展美国社区调查,产生大量数据集。富裕的数据集包含关于他们的详细信息,关于他们是谁以及他们的生活方式,包括祖先,教育,工作,运输,互联网使用等。这种巨大的数据鼓励需要更多地了解人口并获得洞察力。在经济问题的情况下暴露微妙的令人要求苛刻的要求是在收入域中解释有意义结论的动机。因此,重点是专注于将独特的见解纳入居住在该国人民的财务状况。划定的结论界定可能有助于在国内经济增长方面提供更明智的决策。使用相关属性,绘制了人口图,解释了得出的结论。还使用众所周知的分类器进行各种经济舱的分类。

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