Класифікація функціональних даних за допомогою сплайнів з вільними вузлами
Data, obtained through measurements of some process, in many problems, can be treated as functions of a continuous argument. An analysis of such "functional" data is much more complicated than multivariate data analysis. Functional data can be reflected into an appropriate form for traditi...
Збережено в:
| Дата: | 2014 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | Ukrainian |
| Опубліковано: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2014
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| Онлайн доступ: | http://journal.iasa.kpi.ua/article/view/30501 |
| Теги: |
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| Назва журналу: | System research and information technologies |
Репозитарії
System research and information technologies| Резюме: | Data, obtained through measurements of some process, in many problems, can be treated as functions of a continuous argument. An analysis of such "functional" data is much more complicated than multivariate data analysis. Functional data can be reflected into an appropriate form for traditional statistical algorithms with the help of free -knot splines, which causes almost no loss of information. Finding the free knots of spline is a complex optimization problem, so this paper presents a new heuristic method in order to solve it. An equally important step is to select the parameters of the approximation model. To deal with it, we developed a new approach, which is based on multi-objective optimization of computation time and the accuracy of approximation. The use of splines for classification of functional data was demonstrated on the problem of diagnosis of arthritis based on the bone shapes. |
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