期刊
NEUROCOMPUTING
卷 102, 期 -, 页码 52-58出版社
ELSEVIER
DOI: 10.1016/j.neucom.2012.01.040
关键词
Data mining; Regression; ELM; MapReduce; PELM
资金
- National Natural Science Foundation of China [60933004, 60975039, 61175052, 61035003, 61072085]
- National High-tech R&D Program of China (863 Program) [2012AA011003]
Regression is one of the most basic problems in data mining. For regression problem, extreme learning machine (ELM) can get better generalization performance at a much faster learning speed. However, the enlarging volume of datasets makes regression by ELM on very large scale datasets a challenging task. Through analyzing the mechanism of ELM algorithm, an efficient parallel ELM for regression is designed and implemented based on MapReduce framework, which is a simple but powerful parallel programming technique currently. The experimental results demonstrate that the proposed parallel ELM for regression can efficiently handle very large datasets on commodity hardware with a good performance on different evaluation criterions, including speedup, scaleup and sizeup. (C) 2012 Elsevier B.V. All rights reserved.
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