- Tytuł:
- Evolving ensembles of linear classifiers by means of clonal selection algorithm
- Autorzy:
-
Bereta, M.
Burczyński, T. - Powiązania:
- https://bibliotekanauki.pl/articles/969829.pdf
- Data publikacji:
- 2010
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
artificial immune systems
clonal selection
linear classifiers
bagging
boosting - Opis:
- Artificial immune systems (AIS) have become popular among researchers and have been applied to a variety of tasks. Developing supervised learning algorithms based on metaphors from the immune system is still an area in which there is much to explore. In this paper a novel supervised immune algorithm based on clonal selection framework is proposed. It evolves a population of linear classifiers used to construct a set of classification rules. Aggregating strategies, such as bagging and boosting, are shown to work well with the proposed algorithm as the base classifier.
- Źródło:
-
Control and Cybernetics; 2010, 39, 2; 325-342
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki
Artykuł