利用机器学习算法预测H1B签证

Debabrata Swain, Kushankur Chakraborty, A. Dombe, Ashitosh Ashture, N. Valakunde
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引用次数: 5

摘要

H1 - B签证是世界上需求量最大的签证。H1 - B签证申请在许多领域都有很大的差异,例如工作、职位、申请年份、实际工资、工作城市等。本研究的目的是在提供元数据的基础上估计签证批准的可能性。我们会考虑申请可能获批准或不获批准的所有方面,并严格按照申请书所提供的资料进行处理。在后面提到的报告中设计的分类器为H1B申请人和有希望的雇主提供了双重目的,以衡量在申请请愿之前和之后获得认证的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of H1B Visa Using Machine Learning Algorithms
The H1 B visa is the most demanded visa world-wide. The H1 B visa applications are very heavily varied across many fields i.e. job, job title, year of petition, accountable wages, city of work etc. The purpose of this research is to estimate the likelihood of visa approval on the basis of metadata provided. We shall consider all aspects by which the petition may be approved or otherwise, strictly working on the data provided in the application. The designed classifier in the after mentioned report serves a dual purpose of H1B applicants and hopeful employers to measure the probability of getting certified prior to and after applying the petition.
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