- Tytuł:
- GrNFS: A granular neuro-fuzzy system for regression in large volume data
- Autorzy:
- Siminski, Krzysztof
- Powiązania:
- https://bibliotekanauki.pl/articles/2055169.pdf
- Data publikacji:
- 2021
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
granular computing
neuro-fuzzy system
large volume data
machine learning
przetwarzanie ziarniste
system neurorozmyty
uczenie maszynowe - Opis:
- Neuro-fuzzy systems have proved their ability to elaborate intelligible nonlinear models for presented data. However, their bottleneck is the volume of data. They have to read all data in order to produce a model. We apply the granular approach and propose a granular neuro-fuzzy system for large volume data. In our method the data are read by parts and granulated. In the next stage the fuzzy model is produced not on data but on granules. In the paper we introduce a novel type of granules: a fuzzy rule. In our system granules are represented by both regular data items and fuzzy rules. Fuzzy rules are a kind of data summaries. The experiments show that the proposed granular neuro-fuzzy system can produce intelligible models even for large volume datasets. The system outperforms the sampling techniques for large volume datasets.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 445--459
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki