Fuzzy extensions of the DBScan clustering algorithm

The DBSCAN algorithm is a well-known density-based clustering approach particularly useful in spatial data mining for its ability to find objects’ groups with heterogeneous shapes and homogeneous local density distributions in the feature space. Furthermore, it can be suitable as scaling down approa...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Soft computing (Berlin, Germany) Ročník 22; číslo 5; s. 1719 - 1730
Hlavní autori:	Ienco, Dino, Bordogna, Gloria
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2018 Springer Nature B.V Springer Verlag
Edícia:	Methodologies and Application
Predmet:	Algorithms Artificial Intelligence Big Data Borders Clustering Computational Intelligence Computer Science Constraint modelling Control Data mining Datasets Density Engineering Fuzzy sets Information Retrieval Machine Learning Mathematical Logic and Foundations Mechatronics Methodologies and Application Neighborhoods Parameters Robotics Social networks Spatial data Density-based clustering DBSCAN clustering Fuzzy clustering
ISSN:	1432-7643, 1433-7479
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!