Statistical and computational model for high dimensional data analysis

高维数据分析的统计和计算模型

• 批准号: RGPIN-2016-06546
• 负责人: Wong, WilliamWaiLun
• 金额: $ 1.31万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635856
• 关键词: Statistical; computational; model; dimensional; data

Research towards the development of statistical and computational methodologies for analyzing high dimensional data has gained much attention over the last decade. Methodological advances with respect to feature selection, classification, and predication have been widely applied in many fields, such as the drug discovery process, high throughput genomic and genetic data analysis, and infectious disease modeling.

在过去的十年中，对用于分析高维数据的统计和计算方法的研究得到了广泛的关注。在特征选择、分类和预测方面的方法学进展已广泛应用于许多领域，如药物发现过程、高通量基因组和遗传数据分析以及传染病建模。