The fuzzy clustering (fc) package contains well-known algorithms like the fuzzy c-means algorithm and the algorithm by Gustafson and Kessel, but also more recent developments. A number of support tools, including X-windows, OpenGL, or postscript visualization, are also included. The GNU-style package comes along with postscript documentation, however, if you are interested in the algorithms I recommend to read our fuzzy clustering book. The package consists of a number of standalone executeables that can be combined easily on the command line (and on the source code level, if you want to make things faster). Using UNIX pipes and batch files, you can quickly make use of the algorithms within your own application. The utility package is required.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Alonso, Andrés M.; D’Urso, Pierpaolo; Gamboa, Carolina; Guerrero, Vanesa: Cophenetic-based fuzzy clustering of time series by linear dependency (2021)
- De Luca, Giovanni; Zuccolotto, Paola: Regime dependent interconnectedness among fuzzy clusters of financial time series (2021)
- Ferraro, Maria Brigida; Giordani, Paolo: A review and proposal of (fuzzy) clustering for nonlinearly separable data (2019)
- Maria Brigida Ferraro, Paolo Giordani: A toolbox for fuzzy clustering using the R programming language (2015) not zbMATH
- Höppner, Frank; Klawonn, Frank; Kruse, Rudolf; Runkler, Thomas: Fuzzy cluster analysis. Methods for classification, data analysis and image recognition (1999)