图 书 馆
高维共线数据的双向分析Two-Way Analysis of High-Dimensional Collinear Data |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_huopaniemi_twahdcd/ |
| 主讲教师: | Ilkka Huopaniemi |
| 开课单位: | 阿尔托大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a Bayesian model for two-way ANOVA-type analysis of high-dimensional, small sample-size datasets with highly correlated groups of variables. Modern cellular measurement methods are a main application area; typically the task is differential analysis between diseased and healthy samples, complicated by additional covariates requiring a multi-way analysis. The main complication is the combination of high dimensionality and low sample size, which renders classical multivariate techniques useless. We introduce a hierarchical model which does dimensionality reduction by assuming that the input variables come in similarly-behaving groups, and performs an ANOVA-type decomposition for the set of reduced-dimensional latent variables. We apply the methods to study lipidomic profiles of a recent large-cohort human diabetes study. |
| 关 键 词: | 贝叶斯模型; 小样本数据集; 现代蜂窝测量 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-24：cwx |
| 阅读次数: | 74 |