- Tytuł:
- The pair-wise linear classifier and the k-NN rule in application to ALS progression differentiation
- Autorzy:
-
Sokołowska, B.
Jóźwik, A.
Niebroj-Dobosz, I.
Janik, P. - Powiązania:
- https://bibliotekanauki.pl/articles/333011.pdf
- Data publikacji:
- 2012
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
rozpoznawanie wzorców
wybór funkcji
klasyfikator liniowy
zasada k-NN
biomarkery
stwardnienie zanikowe boczne
pattern recognition
feature selection
linear classifier
k-NN rule
pair-wise classifier
biomarkers
amyotrophic lateral sclerosis - Opis:
- The two kinds of classifier based on the k-NN rule, the standard and the parallel version, were used for recognition of severity of ALS disease. In case of the second classifier version, feature selection was done separately for each pair of classes. The error rate, estimated by the leave one out method, was used as a criterion as for determination the optimum values of k's as well as for feature selection. All features selected in this manner were used in the standard and in the parallel classifier based on k-NN rule. Furthermore, only for the verification purpose, the linear classifier was applied. For this kind of classifier the error rates were calculated by use the training set also as a testing one. The linear classifier was trained by the error correction algorithm with a modified stop condition. The data set concerned with the healthy subjects and patients with amyotrophic lateral sclerosis (ALS). The set of several biomarkers such as erythropoietin, matrix metalloproteinases and their tissue inhibitors measured in serum and cerebrospinal fluid (CSF) were treated as features. It was shown that CSF biomarkers were very sensitive for the ALS progress.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2012, 20; 79-83
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł