عنوان انگلیسی مقاله:
Use of support vector machines with a parallel local search algorithm for data classification and feature selection
ترجمه فارسی عنوان مقاله:
استفاده از ماشینهای بردار پشتیبانی با الگوریتم جستجوی محلی موازی برای طبقه بندی داده ها و انتخاب ویژگی ها
Sciencedirect - Elsevier - Expert Systems With Applications, 145 (2020) 113133: doi:10:1016/j:eswa:2019:113133
Over the last decade, the number of studies on machine learning has significantly increased. One of the most widely researched areas of machine learning is data classification. Most big data systems require a large amount of information storage for analytic purposes; however, this involves some disadvantages, such as the costs of processing and collecting data. Thus, many researchers and practitioners are working on effectively reducing the number of features used in classification. This paper proposes a method which jointly optimizes both feature selection and classification. A survey of the relevant literature shows that the vast majority of studies focus on either feature selection or classification. In this study, the proposed parallel local search algorithm both selects features and finds a classifier with high rates of accuracy. Moreover, the proposed method is capable of finding solutions for problems that have extremely high numbers of features within a reasonable computation time.
Keywords: Support vector machines | Feature selection | Classification | Heuristic | Machine learning