ConsRankClass - Classification and Clustering of Preference Rankings
Tree-based classification and soft-clustering method for
preference rankings, with tools for external validation of
fuzzy clustering, and Kemeny-equivalent augmented unfolding. It
contains the recursive partitioning algorithm for preference
rankings, non-parametric tree-based method for a matrix of
preference rankings as a response variable. It contains also
the distribution-free soft clustering method for preference
rankings, namely the K-median cluster component analysis (CCA).
The package depends on the 'ConsRank' R package. Options for
validate the tree-based method are both test-set procedure and
V-fold cross validation. The package contains the routines to
compute the adjusted concordance index (a fuzzy version of the
adjusted rand index) and the normalized degree of concordance
(the corresponding fuzzy version of the rand index). The
package also contains routines to perform the Kemeny-equivalent
augmented unfolding. The mds endine is the function 'sacofSym'
from the package 'smacof'. Essential references: D'Ambrosio,
A., Vera, J.F., and Heiser, W.J. (2021)
<doi:10.1080/00273171.2021.1899892>; D'Ambrosio, A., Amodio,
S., Iorio, C., Pandolfo, G., and Siciliano, R. (2021)
<doi:10.1007/s00357-020-09367-0>; D'Ambrosio, A., and Heiser,
W.J. (2019) <doi:10.1007/s41237-018-0069-5>; D'Ambrosio, A.,
and Heiser W.J. (2016) <doi:10.1007/s11336-016-9505-1>;
Hullermeier, E., Rifqi, M., Henzgen, S., and Senge, R. (2012)
<doi:10.1109/TFUZZ.2011.2179303>; Marden, J.J.
<ISBN:0412995212>.
