Mixture models for high-dimensional clustering with applications to tumour classification, network intrusion, and text classification

用于高维聚类的混合模型及其在肿瘤分类、网络入侵和文本分类中的应用

• 批准号: DP0879814
• 负责人: Prof Geoffrey McLachlan
• 金额: $ 15.26万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0879814
• 关键词: Mixture; models; dimensional; clustering; applications

This project will benefit the Australian Society as a whole by developing statistical methodology for the clustering of high-dimensional data. In particular, it will develop a novel and efficient model for extracting useful information from subpopulations. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to classify brain tumours and detect network intruders. This cross-disciplinary project will contribute to Australia's economic of public health, protect Australia from crime, and strength Australian researchers' capacity and capability of participating in this emerging science.

该项目将为高维数据的分类开发统计方法，从而使整个澳大利亚社会受益。特别是，它将开发一种从子种群中提取有用信息的新颖而有效的模型。因此，它对提高澳大利亚大多数行业的应用研究的质量和有效性具有广泛的适用性。更具体地说，它将在这里应用于脑瘤分类和检测网络入侵者。这一跨学科项目将有助于澳大利亚的经济和公共卫生，保护澳大利亚不受犯罪的影响，并增强澳大利亚研究人员参与这一新兴科学的能力和能力。