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基于树和树集合的多目标预测

Multi-Target Prediction with Trees and Tree Ensembles
课程网址: http://videolectures.net/icgeb_dzeroski_multi_target_prediction/  
主讲教师: Sašo Džeroski
开课单位: Joíef Stefan Institute智能系统部
开课时间: 2019-09-19
课程语种: 英语
中文简介:
我们越来越需要从大数据或复杂数据中学习预测模型,这些数据可能包含许多示例和许多输入/输出维度。当必须预测多个目标变量时,我们讨论多目标预测。预测建模问题在其他方面也可能很复杂,例如,它们可能涉及不完全/部分标记的数据,如半监督学习中的数据,或放置在网络环境中的数据。演讲首先介绍多目标预测的不同任务,如多目标分类和回归、其分层版本,以及涉及额外复杂性的任务版本(如半监督多目标回归和基于网络的分层多标签分类)。它将继续介绍解决此类任务的方法,特别是预测聚类树及其集合。最后,它将介绍多目标预测在生命科学中的示例应用,重点是预测建模在药物再利用的虚拟化合物筛选中的应用。
课程简介: Increasingly often, we need to learn predictive models from big or complex data, which may comprise many examples and many input/output dimensions. When more than one target variable has to be predicted, we talk about multi-target prediction. Predictive modeling problems may also be complex in other ways, e.g., they may involve incompletely/partially labelled data, as in semi-supervised learning, or data placed in a network context. The talk will first give an introduction to the different tasks of multi-target prediction, such as multi-target classification and regression, hierarchical versions thereof, and versions of the tasks that involve additional complexity (such as semi-supervised multi-target regression and network-based hierarchical multi-label classification). It will continue to present methods for solving such tasks, in particular predictive clustering trees and ensembles thereof. Finally, it will present example applications of multi-target prediction in the life sciences, focusing on predictive modeling in virtual compound screening for drug repurposing.
关 键 词: 基于树和树集合; 数据科学; 多目标预测; 预测聚类树及其集合; 复杂数据中学习预测模型
课程来源: 视频讲座网
数据采集: 2022-10-14:cyh
最后编审: 2022-10-14:cyh
阅读次数: 41