کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4947094 | 1439565 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An online classification algorithm for large scale data streams: iGNGSVM
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Stream Processing has recently become one of the current commercial trends to face huge amounts of data. However, normally these techniques need specific infrastructures and high resources in terms of memory and computing nodes. This paper shows how mini-batch techniques and topology extraction methods can help making gigabytes of data to be manageable for just one server using computationally costly Machine Learning techniques as Support Vector Machines. The algorithm iGNGSVM is proposed to improve the performance of Support Vector Machines in datasets where the data is continuously arriving. It is benchmarked against a mini-batch version of LibSVM, achieving good accuracy rates and performing faster than this.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 262, 1 November 2017, Pages 67-76
Journal: Neurocomputing - Volume 262, 1 November 2017, Pages 67-76
نویسندگان
Andrés L. Suárez-Cetrulo, Alejandro Cervantes,