文章基本信息

标题：Robust Scalable Algorithm Applied to Real World Problem
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作者：Byung Joo Kim
期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2015
卷号：10
期号：9
页码：91-98
DOI：10.14257/ijmue.2015.10.9.10
出版社：SERSC
摘要：Advances in digital sensors, communications, computation, and storage have created huge collections of data, capturing information of value to business, science, government, and society. Many machine learning algorithms do not scale beyond data sets of a few million elements or cannot tolerate the statistical noise and gaps found in real-world data. Further research is required to develop algorithms that apply in real-world situations and on data sets of trillions of elements. In this paper we propose a conjugate based novel algorithm to handle the huge collections of data. Through the experimental results, proposed method performs well on huge data from UCI machine learning repository data Set.
关键词：Conjugate Method; LS-SVM; Support Vector Machine