- Tytuł:
- Influence of missing data imputation method on the classification accuracy of the medical data
- Autorzy:
-
Orczyk, T.
Porwik, P. - Powiązania:
- https://bibliotekanauki.pl/articles/334037.pdf
- Data publikacji:
- 2013
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
medical data analysis
missing data
data imputation
classification efficiency
analiza danych medycznych
brakujące dane
przypisanie danych
efektywność klasyfikacji - Opis:
- Aim of this study is to show the dangers of filling missing data - particularly medical data. Because there are many dedicated medical expert systems and medical decision support systems, a special attention must be paid on the construction of classifiers. Medical data are almost never complete, and completion of the missing data requires a special care. The safest approach of dealing with missing data would be removing records with missing parameters and/or removing parameters that are missing in the records. Unfortunately reducing data set that is already very small is not always an option. Dangers coming out from data imputation are shown in the article, which presents the influence of selected missing data filling algorithms on the classification accuracy.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2013, 22; 111-116
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł