The soft (“fuzzy”) consensus partitions for the macroeconomic partition data given in Gordon and Vichi (2001).
A named cluster ensemble of eight soft partitions of 21 countries terms into two or three classes.
The elements of the ensemble are consensus partitions for the
macroeconomic partition data in Gordon and Vichi (2001), which are
available as data set
GVME. Element names are of the
"m/k", where m indicates the consensus
method employed (one of MF1, MF2, JMF, and
S&S, corresponding to the application of models 1, 2, and 3
in Gordon and Vichi (2001) and the approach in Sato and Sato (1994),
respectively), and k denotes the number classes (2 or 3).
Tables 4 and 5 in Gordon and Vichi (2001).
A. D. Gordon and M. Vichi (2001). Fuzzy partition models for fitting a set of partitions. Psychometrika, 66, 229–248. doi: 10.1007/BF02294837.
M. Sato and Y. Sato (1994).
On a multicriteria fuzzy clustering method for 3-way data.
International Journal of Uncertainty, Fuzziness and
Knowledge-Based Systems, 2, 127–142.
1 2 3 4 5 6 7 8 9 10
## Load the consensus partitions. data("GVME_Consensus") ## Pick the partitions into 2 classes. GVME_Consensus_2 <- GVME_Consensus[1 : 4] ## Fuzziness using the Partition Coefficient. cl_fuzziness(GVME_Consensus_2) ## (Corresponds to 1 - F in the source.) ## Dissimilarities: cl_dissimilarity(GVME_Consensus_2) cl_dissimilarity(GVME_Consensus_2, method = "comem")