图 书 馆
基于概率预测的支持向量回归机特征选择Feature Selection for Support Vector Regression Using Probabilistic Prediction |
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| 课程网址: | http://videolectures.net/kdd2010_yang_fssv/ |
| 主讲教师: | Jian-Bo Yang |
| 开课单位: | 新加坡国立大学 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper presents a novel wrapper-based feature selection method for Support Vector Regression (SVR) using its probabilistic predictions. The method computes the importance of a feature by aggregating the difference, over the feature space, of the conditional density functions of the SVR prediction with and without the feature. As the exact computation of this importance measure is expensive, two approximations are proposed. The effectiveness of the measure using these approximations, in comparison to several other existing feature selection methods for SVR, is evaluated on both artificial and real-world problems. The result of the experiment shows that the proposed method generally performs better, and at least as well as the existing methods, with notable advantage when the data set is sparse. |
| 关 键 词: | 数据挖掘; 人工智能; 计算机科学; 支持向量回归 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-18：cwx |
| 阅读次数: | 24 |