رگرسیون بردار پشتیبان بر اساس نمونه مجموعه ارزش و کاربردهای آن
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|46631||2015||8 صفحه PDF||سفارش دهید||6761 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 42, Issue 5, 1 April 2015, Pages 2502–2509
In this study, we address the regression problem on set-valued samples that appear in applications. To solve this problem, we propose a support vector regression approach for set-valued samples that generalizes the classical ε-support vector regression. First, an initial representative point (or an element) for every set-valued sample is selected, and a weighted distance between the initial representative point and other points is determined. Second, based on the classification consistency principle, a search algorithm to determine the best representative point for every set-valued datum is designed. Thus, the set-valued samples are converted into numeric samples. Finally, a support vector regression that is based on set-valued data is constructed, and the regression results of the set-valued samples can be approximated using the method used for the numeric samples. Furthermore, the feasibility and efficiency of the proposed method is demonstrated using experiments with real-world examples concerning wind speed prediction and the prediction of peak particle velocity.