symbolicDA

Analysis of Symbolic Data

Symbolic data analysis methods: importing/exporting data from ASSO XML Files, distance calculation for symbolic data (Ichino-Yaguchi, de Carvalho measure), zoom star plot, 3d interval plot, multidimensional scaling for symbolic interval data, dynamic clustering based on distance matrix, HINoV method for symbolic data, Ichino's feature selection method, principal component analysis for symbolic interval data, decision trees for symbolic data based on optimal split with bagging, boosting and random forest approach (+visualization), kernel discriminant analysis for symbolic data, Kohonen's self-organizing maps for symbolic data, replication and profiling, artificial symbolic data generation. (Milligan, G.W., Cooper, M.C. (1985) <doi:10.1007/BF02294245>, Breiman, L. (1996), <doi:10.1007/BF00058655>, Hubert, L., Arabie, P. (1985), <doi:10.1007%2FBF01908075>, Ichino, M., & Yaguchi, H. (1994), <doi:10.1109/21.286391>, Rand, W.M. (1971) <doi:10.1080/01621459.1971.10482356>, Calinski, T., Harabasz, J. (1974) <doi:10.1080/03610927408827101>, Breckenridge, J.N. (2000) <doi:10.1207/S15327906MBR3502_5>, Groenen, P.J.F, Winsberg, S., Rodriguez, O., Diday, E. (2006) <doi:10.1016/j.csda.2006.04.003>, Walesiak, M., Dudek, A. (2008) <doi:10.1007/978-3-540-78246-9_11>, Dudek, A. (2007), <doi:10.1007/978-3-540-70981-7_4>).

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Description file content

Package
symbolicDA
Title
Analysis of Symbolic Data
Version
0.6-2
Date
2019-08-07
Author
Andrzej Dudek, Marcin Pelka , Justyna Wilk (to 2017-09-20), Marek Walesiak (from 2018-02-01)
Maintainer
Andrzej Dudek
Depends
R(>= 3.6.0), clusterSim,XML
Imports
rgl, shapes, e1071, ade4, cluster, RSDA
Description
Symbolic data analysis methods: importing/exporting data from ASSO XML Files, distance calculation for symbolic data (Ichino-Yaguchi, de Carvalho measure), zoom star plot, 3d interval plot, multidimensional scaling for symbolic interval data, dynamic clustering based on distance matrix, HINoV method for symbolic data, Ichino's feature selection method, principal component analysis for symbolic interval data, decision trees for symbolic data based on optimal split with bagging, boosting and random forest approach (+visualization), kernel discriminant analysis for symbolic data, Kohonen's self-organizing maps for symbolic data, replication and profiling, artificial symbolic data generation. (Milligan, G.W., Cooper, M.C. (1985) , Breiman, L. (1996), , Hubert, L., Arabie, P. (1985), , Ichino, M., & Yaguchi, H. (1994), , Rand, W.M. (1971) , Calinski, T., Harabasz, J. (1974) , Breckenridge, J.N. (2000) , Groenen, P.J.F, Winsberg, S., Rodriguez, O., Diday, E. (2006) , Walesiak, M., Dudek, A. (2008) , Dudek, A. (2007), ).
License
GPL (>= 2)
URL
Encoding
UTF-8
NeedsCompilation
no
Packaged
2019-08-07 12:19:23 UTC; andrzej
Repository
CRAN
Date/Publication
2019-08-08 15:30:03 UTC

install.packages('symbolicDA')

0.6-2

4 months ago

http://keii.ue.wroc.pl/symbolicDA

Andrzej Dudek

GPL (>= 2)

Depends on

R(>= 3.6.0), clusterSim,XML

Imports

rgl, shapes, e1071, ade4, cluster, RSDA

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