PPCI

Projection Pursuit for Cluster Identification

Implements recently developed projection pursuit algorithms for finding optimal linear cluster separators. The clustering algorithms use optimal hyperplane separators based on minimum density, Pavlidis et. al (2016) <https://jmlr.csail.mit.edu/papers/volume17/15-307/15-307.pdf>; minimum normalised cut, Hofmeyr (2017) <doi:10.1109/TPAMI.2016.2609929>; and maximum variance ratio clusterability, Hofmeyr and Pavlidis (2015) <doi:10.1109/SSCI.2015.116>.

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Description file content

Package
PPCI
Type
Package
Title
Projection Pursuit for Cluster Identification
Version
0.1.3
Author
David Hofmeyr [aut, cre] Nicos Pavlidis [aut]
Maintainer
David Hofmeyr
Description
Implements recently developed projection pursuit algorithms for finding optimal linear cluster separators. The clustering algorithms use optimal hyperplane separators based on minimum density, Pavlidis et. al (2016) ; minimum normalised cut, Hofmeyr (2017) ; and maximum variance ratio clusterability, Hofmeyr and Pavlidis (2015) .
Depends
R (>= 2.10.0), rARPACK
License
GPL-3
Encoding
UTF-8
LazyData
yes
RoxygenNote
6.1.0
NeedsCompilation
no
Packaged
2018-10-08 09:51:40 UTC; dhofmeyr
Repository
CRAN
Date/Publication
2018-10-08 10:10:10 UTC

install.packages('PPCI')

0.1.3

11 days ago

David Hofmeyr

GPL-3

Depends on

R (>= 2.10.0), rARPACK

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