图 书 馆
一种有效的无参数大规模离线学习方法An Efficient Parameter - Free Method for Large Scale Offline Learning |
|
| 课程网址: | http://videolectures.net/icml08_boulle_aep/ |
| 主讲教师: | Marc Boulle |
| 开课单位: | 法国电信研究院 |
| 开课时间: | 2008-09-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | With the rapid growth of computer storage capacities, available data and demand for scoring models both follow an increasing trend, sharper than that of the processing power. However, the main limitation to a wide spread of data mining solutions is the non-increasing availability of skilled data analysts, which play a key role in data preparation and model selection. In this paper we present a parameter-free scalable classification method, which is a step towards fully automatic data mining. The method is based on Bayes optimal univariate conditional density estimators, naive Bayes classification enhanced with a Bayesian variable selection scheme, and averaging of models using a logarithmic smoothing of the posterior distribution. We focus on the complexity of the algorithms and show how they can cope with datasets that are far larger than the available central memory. We finally report results on the Large Scale Learning challenge, where our method obtains state of the art performance within practicable computation time. |
| 关 键 词: | 数据挖掘; 可用数据; 贝叶斯变量选择方案 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-17：lxf |
| 阅读次数: | 46 |