Building flexible tree models and ensemble tree models for statistical learning in classification, regression and failure time data analysis

构建灵活的树模型和集成树模型，用于分类、回归和故障时间数据分析中的统计学习

• 批准号: 311980-2008
• 负责人: Fan, Guangzhe
• 金额: $ 1.02万
• 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: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=396597
• 关键词: Building; flexible; tree; models; ensemble

My proposed research is mainly in the direction of building flexible tree models and ensemble tree models for statistical learning in classification, regression and the statistical analysis of failure time data. The proposed research is expected to improve the information learning and prediction in physics, chemistry, drug discovery, biology, engineering and health sciences.

我提出的研究方向主要是在故障时间数据的分类、回归和统计分析中，建立用于统计学习的柔性树模型和集成树模型。该研究有望改善物理、化学、药物发现、生物、工程和健康科学领域的信息学习和预测。