摘要
新闻编辑从发明者提供的背景信息中获得了以下引文：“机器学习模型可以用于基于各种领域的预测做出决策，例如金融服务、医疗保健、教育、人力资源等。机器学习模型的开发和使用提供了更高的生产力和成本节约，并得到了收集、汇总、并处理大量数据，例如，使用云计算和物联网(IoT)。使用收集的和聚集的数据训练机器学习模型以进行预测。数据可以包括与一个或多个实体相关的观察，可能是时间的函数。在某些情况下，数据可以以各种方式进行预处理，例如，为了消除不完全的观察。每个实体都可能是一个企业的人。在某些应用领域，理解为什么Mac Hine学习模型会对观察结果做出预测，以及预测结果是否受到任何偏差的影响是很重要的。
Abstract
The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Machine learning models may be used to make dec isions based on predictions across various domains such as financial services, h ealthcare, education, human resources, etc. The development and use of machine l earning models provide increased productivity and cost savings and are supported by the ability to collect, aggregate, and process large amounts of data, for ex ample, using cloud computing and the Internet of things (IoT). Machine learning models are trained using the collected and aggregated data to make predictions. The data may include observations related to one or more entities possibly as a function of time. In some cases, the data may be pre-processed in various manner s, for example, to remove incomplete observations. Each entity may be a person o r a business. In some application areas, it is important to understand why a mac hine learning model made a prediction for an observation and whether the predict ion was impacted by any bias.
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NSTL