کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1136757 | 1489138 | 2013 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evidence optimization for consequently generated models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Evidence optimization for consequently generated models Evidence optimization for consequently generated models](/preview/png/1136757.png)
چکیده انگلیسی
To construct an adequate regression model one has to fulfill the set of measured features with their generated derivatives. Often the number of these features exceeds the number of the samples in the data set. After a feature generation process the problem of feature selection from a set of highly correlated features arises. The proposed algorithm uses an evidence maximization procedure to select a model as a subset of generated features. During the selection process it rejects multicollinear features. A problem of European option volatility modeling illustrates the algorithm. Its performance is compared with the performances of similar well-known algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 57, Issues 1–2, January 2013, Pages 50–56
Journal: Mathematical and Computer Modelling - Volume 57, Issues 1–2, January 2013, Pages 50–56
نویسندگان
Vadim Strijov, Ekaterina Krymova, Gerhard Wilhelm Weber,