摘要
由一名新闻记者兼机器人与机器学习每日新闻编辑-调查人员讨论机器学习的新发现。据NewsRx记者从哥伦比亚波哥大发回的新闻报道，研究表明：“在过去十年中，由于数据和计算资源的可获得性不断提高，机器学习(ML)方法开始在扶持行动政策和方案的实施中发挥关键作用。其基本假设是，资源分配可以通过预测个人风险来进行。”改善潜在受益人的优先次序，并提高系统的绩效。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news originating from Bogota, Colombia, by NewsRx correspondents, research stated, “Over the last decade, due to the growing availability of data and computational resources, machine learning (ML) approaches h ave started to play a key role in the implementation of affirmative-action policies and programs. The underlying assumption is that resource allocation can be informed by the prediction of individual risks, improving the prioritization of t he potential beneficiaries, and increasing the performance of the system.”
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