Investigators from University of Turku Report New Data on Machine Learning (Addr essing Imbalanced Data for Machine Learning Based Mineral Prospectivity Mapping)
Investigators from University of Turku Report New Data on Machine Learning (Addr essing Imbalanced Data for Machine Learning Based Mineral Prospectivity Mapping)
图尔库大学的研究人员报告了机器学习的新数据(为基于机器学习的矿物前景图添加不平衡数据)
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摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。根据新闻报道NewsRx Jour Nalist在芬兰图尔库发表的研究报告称，“有效的矿产远景测绘”(MPM)依靠机器学习(ML)模型的能力从中提取有意义的模式地球物理数据。然而,在矿产勘查中,识别矿床的存在往往是一个非常重要的问题与整体地质景观相比，罕见事件。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reportingfrom Turku, Finland, by NewsRx jour nalists, research stated, “Effective Mineral Prospectivity Mapping(MPM) relies on the ability of Machine Learning (ML) models to extract meaningful patterns fr omgeophysical data. However, in mineral exploration, identifying the presence o f mineral deposits is often arare event compared with the overall geological la ndscape.”
Key words
Turku/Finland/Europe/Cyborgs/Emergin g Technologies/Machine Learning/University of Turku
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