图 书 馆
利用随机森林识别特征相关性Identifying Feature Relevance using a Random Forest |
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| 课程网址: | http://videolectures.net/slsfs05_rogers_ifrur/ |
| 主讲教师: | Jeremy D. Rogers |
| 开课单位: | 南安普敦大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many feature selection algorithms are limited in that they attempt to identify relevant feature subsets by examining the features individually. This paper introduces a technique for determining feature relevance using the average information gain achieved during the construction of decision tree ensembles. The technique introduces a node complexity measure and a statistical method for updating the feature sampling distribution based upon confidence intervals to control the rate of convergence. Experiments demonstrate the potential of this method for feature selection and subspace identification. |
| 关 键 词: | 特征选择算法; 特征子集; 决策树 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 167 |