visualizing the random forest by 3d techniques

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
ISSN	1865-0929
ISBN	9783642324260
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.