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

Target-agnostic analytics: building agile predictive models for big data
与目标无关的分析:为大数据构建敏捷的预测模型
批准号:
DP190100017
负责人:
Prof Geoffrey Webb
金额:
$22.12万
依托单位:
依托单位国家:
澳大利亚
项目类别:
Discovery Projects
财政年份:
2019
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2019-04-01 至 2022-06-30

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中文摘要
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英文摘要
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.
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