- Tytuł:
- Rough support vector machine for classification with interval and incomplete data
- Autorzy:
-
Nowicki, Robert K.
Grzanek, Konrad
Hayashi, Yoichi - Powiązania:
- https://bibliotekanauki.pl/articles/91559.pdf
- Data publikacji:
- 2020
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
support vector machines
rough sets
missing features
interval data
three–way decision
maszyna wektorów nośnych
dane interwałowe - Opis:
- The paper presents the idea of connecting the concepts of the Vapnik’s support vector machine with Pawlak’s rough sets in one classification scheme. The hybrid system will be applied to classifying data in the form of intervals and with missing values [1]. Both situations will be treated as a cause of dividing input space into equivalence classes. Then, the SVM procedure will lead to a classification of input data into rough sets of the desired classes, i.e. to their positive, boundary or negative regions. Such a form of answer is also called a three–way decision. The proposed solution will be tested using several popular benchmarks.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 47-56
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł