ISCAS OpenIR
visualizing the random forest by 3d techniques
Yang Min; Xu Hexin; Zhu Dingju; Chen Huijuan
2012
会议名称International Workshop on Internet of Things, IOT 2012
会议录名称Communications in Computer and Information Science
页码639-645
会议日期August 17, 2012 - August 29, 2012
会议地点Changsha, China
收录类别EI
ISSN1865-0929
ISBN9783642324260
部门归属(1) Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China; (2) School of Software Sichuan University China
摘要Random forest which contains a set of decision trees is a popular method in data mining. It has the advantages of high accuracy, high learning speed and the ability of dealing with high dimensional data. The decision model from the training process, however, is non-deterministic because of the sampling process. Although we can calculate correlations between different decision trees to infer the performance, it's not comprehensive to non-specialists. So, the goal of this project is to find a way of visualizing the learning process and the final model using 3D techniques. As a consequence, it can help in model selection by visualizing the patterns of different trees in terms of density, similarity and so on. Moreover, it can help users to understand how rules are learnt and then applied in decision making. Finally, it can provide an interactive interface for manual modifications (e.g. pruning). © 2012 Springer-Verlag.; Random forest which contains a set of decision trees is a popular method in data mining. It has the advantages of high accuracy, high learning speed and the ability of dealing with high dimensional data. The decision model from the training process, however, is non-deterministic because of the sampling process. Although we can calculate correlations between different decision trees to infer the performance, it's not comprehensive to non-specialists. So, the goal of this project is to find a way of visualizing the learning process and the final model using 3D techniques. As a consequence, it can help in model selection by visualizing the patterns of different trees in terms of density, similarity and so on. Moreover, it can help users to understand how rules are learnt and then applied in decision making. Finally, it can provide an interactive interface for manual modifications (e.g. pruning). © 2012 Springer-Verlag.
关键词Classification (Of Information) Data Mining Decision Making Decision Trees Internet Three Dimensional Computer Graphics Visualization
语种英语
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/15948
专题中国科学院软件研究所
推荐引用方式
GB/T 7714
Yang Min,Xu Hexin,Zhu Dingju,et al. visualizing the random forest by 3d techniques[C],2012:639-645.
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