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https://elib.bsu.by/handle/123456789/233372Полная запись метаданных
| Поле DC | Значение | Язык |
|---|---|---|
| dc.contributor.author | Mangalova, E. | |
| dc.contributor.author | Chubarova, O. | |
| dc.contributor.author | Melekh, D. | |
| dc.date.accessioned | 2019-10-29T12:06:17Z | - |
| dc.date.available | 2019-10-29T12:06:17Z | - |
| dc.date.issued | 2019 | |
| dc.identifier.citation | Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the Twelfth Intern. Conf., Minsk, Sept. 18-22, 2019. – Minsk : BSU, 2019. – P. 232-236. | |
| dc.identifier.isbn | 978-985-566-811-5 | |
| dc.identifier.uri | http://elib.bsu.by/handle/123456789/233372 | - |
| dc.description.abstract | The small sample size problem is often encountered in data analysis, especially for medical applications. It leads to unstable predictions when including or excluding several observations could change prediction significantly. Prediction stability visualization and measure were proposed and applied to estimation of acute pancreatitis severity. A simulation experiments were carried out to study the stability of ridge-regression, SVM, random forest trained with various subsets | |
| dc.language.iso | en | |
| dc.publisher | Minsk : BSU | |
| dc.subject | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика | |
| dc.subject | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика | |
| dc.title | Influence of the training set on the prediction stability in estimation of acute pancreatitis severity | |
| dc.type | conference paper | |
| Располагается в коллекциях: | 2019. Computer Data Analysis and Modeling : Stochastics and Data Science | |
Полный текст документа:
| Файл | Описание | Размер | Формат | |
|---|---|---|---|---|
| 232-236.pdf | 446,57 kB | Adobe PDF | Открыть |
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