visualizing the random forest by 3d techniques
文献类型：会议论文
| 作者 | Yang Min ; Xu Hexin ; Zhu Dingju ; Chen Huijuan |
| 出版日期 | 2012 |
| 会议名称 | International Workshop on Internet of Things, IOT 2012 |
| 会议日期 | August 17, 2012 - August 29, 2012 |
| 会议地点 | Changsha, China |
| 关键词 | Classification (of information) Data mining Decision making Decision trees Internet Three dimensional computer graphics Visualization |
| 页码 | 639-645 |
| 中文摘要 | 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. |
| 英文摘要 | 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. |
| 收录类别 | EI |
| 会议录 | Communications in Computer and Information Science
 |
| 语种 | 英语 |
| ISSN号 | 1865-0929 |
| ISBN号 | 9783642324260 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15948]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 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]. 见:International Workshop on Internet of Things, IOT 2012. Changsha, China. August 17, 2012 - August 29, 2012. |
入库方式： OAI收割
来源：软件研究所
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