funHDDC - Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces
The funHDDC algorithm allows to cluster functional univariate (Bouveyron and Jacques, 2011, <doi:10.1007/s11634-011-0095-6>) or multivariate data (Schmutz et al., 2018) by modeling each group within a specific functional subspace.
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3.21 score 3 stars 27 scripts 539 downloadsordinalClust - Ordinal Data Clustering, Co-Clustering and Classification
Ordinal data classification, clustering and co-clustering using model-based approach with the BOS (Binary Ordinal Search) distribution for ordinal data (Christophe Biernacki and Julien Jacques (2016) <doi:10.1007/s11222-015-9585-2>).
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openblascpp
2.32 score 21 scripts 545 downloadsmixedClust - Co-Clustering of Mixed Type Data
Implementation of the co-clustering method for mixed type data proposed in M. Selosse, J. Jacques, C. Biernacki (2018) <https://hal.science/hal-01893457>. It consists in clustering simultaneously the rows (observations) and the columns (features) of a heterogeneous data set.
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openblascpp
2.00 score 1 stars 2 scripts 127 downloads