A library for locally weighted projection regression

被引：0
|
作者：
Klanke, Stefan [1 ]
Vijayakumar, Sethu [1 ]
Schaal, Stefan [2 ]
机构：
[1] Univ Edinburgh, Sch Informat, Edinburgh EH9 3JZ, Midlothian, Scotland
[2] Univ So Calif, Dept Comp Sci, Los Angeles, CA 90089 USA
来源：
JOURNAL OF MACHINE LEARNING RESEARCH | 2008年 / 9卷
关键词：
regression; local learning; online learning; C; C plus; Matlab; Octave; !text type='Python']Python[!/text;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensional input data. As the key features, our code supports multi-threading, is available for multiple platforms, and provides wrappers for several programming languages.
引用
收藏
页码：623 / 626
页数：4
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