- Tytuł:
- An implementation of articial advisor for dynamic classication of objects
- Autorzy:
-
Łukawska, B.
Łukawski, G.
Sapiecha, K. - Powiązania:
- https://bibliotekanauki.pl/articles/106248.pdf
- Data publikacji:
- 2016
- Wydawca:
- Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
- Tematy:
-
rfc
ACA
database - Opis:
- The paper presents an original method of dynamic classication of objects from a new domain which lacks an expert knowledge. The method relies on analysis of attributes of objects being classied and their general quality Q, which is a combination of particular object's attributes. The method uses a test of normality as a basis for computing the reliability factor of the classication (rfc), which indicates whether the classication and the model of quality Q are reliable. There is no need to collect data about all objects before the classication starts and possibly the best objects ale selected dynamically (on-the-y) while data concerning consecutive objects are gathered. The method is implemented as a software tool called Articial Classication Adviser (ACA). Moreover, the paper presents a case study, where the best candidates for reghting mobile robot operators are selected.
- Źródło:
-
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2016, 16, 1; 40-49
1732-1360
2083-3628 - Pojawia się w:
- Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
- Dostawca treści:
- Biblioteka Nauki
Artykuł