期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2016
卷号：8
期号：1
出版社：International Center for Scientific Research and Studies
摘要：The big data era has become known for its abundance in rapidlygenerated data of varying formats and sizes. With this awareness,interest in data analytics and more specifically predictive analyticshas received increased attention lately. However, the massive samplesizes and high dimensionality peculiar with these datasets haschallenged the overall performance of one of the most importantcomponents of predictive analytics of our present time, MachineLearning. Given that dimensionality reduction has been heavilyapplied to the problems of high dimensionality, this work presents animproved scheme of GPU based Multiple Back Propagation (MBP)with feature selection for big high dimensional data problems.Elastic Net was used for automatic feature selection of highdimensional biomedical datasets before classification with GPUbased MBP and experimental results show an improved performanceover the previous scheme with MBP
关键词：Big data; GPU; Multiple Back Propagation; Feature Selection.
