Target-agnostic analytics: building agile predictive models for big data

该项目旨在开发目标不可知的分析，创建可以查询任何变量或特征的数据模型，而无需重新学习。政府和企业收集了大量的数据，但如果我们不能利用它们从过去预测未来，这些数据就被浪费了。目前，大数据分析在预测单个预定义目标变量方面是有效的，但在许多应用中，我们对系统的了解以及我们想要发现的东西要复杂得多。该项目预计将产生新的目标不可知技术与相关的出版物和开源软件。该项目将扩展机器学习的能力，更好地利用在大多数公共、商业和工业部门收集的大量数据资产。

This project aims to develop target-agnostic analytics, creating models of data that can be queried about any variable or feature without having to be relearned. Government and business collect vast quantities of data, but these are wasted if we cannot use them to predict the future from the past. Presently, big-data analytics is effective at predicting a single pre-defined target variable, yet in many applications, what we know about a system and what we want to find out are far more complex. This project expects to yield novel target-agnostic technologies with associated publications and open-source software. The project will expand the capabilities of machine learning, providing better use of the massive data assets collected across most public, commercial and industry sectors.