首页|Study Results from Huaqiao University Update Understanding of Machine Learning ( Analyzing the Differential Impact of Variables On the Success of Solicited and U nsolicited Private Participation In Infrastructure Projects Using Machine Learni ng ...)
Study Results from Huaqiao University Update Understanding of Machine Learning ( Analyzing the Differential Impact of Variables On the Success of Solicited and U nsolicited Private Participation In Infrastructure Projects Using Machine Learni ng ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. In the study, a machine learning framework has been used to highligh t the variables important for solicited and unsolicited projects.”Our news journalists obtained a quote from the research from Huaqiao University, “The framework addresses the data-related challenges using imputation, oversamp ling and standardization techniques. Further, it uses Random forest, Artificial neural network and Logistics regression for classification and a group of divers e metrics for assessing the performances of these classifiers.FindingsThe result s show that around half of the variables similarly impact both solicited and uns olicited projects. However, some other important variables, particularly, instit utional factors, have different levels of impact on both projects, which have be en previously ignored.”
QuanzhouPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningHuaqiao University
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