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) <http://jmlr.org/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>.
| Version: | 0.1.5 |
| Depends: | R (≥ 2.10.0), rARPACK |
| Published: | 2020-03-06 |
| Author: | David Hofmeyr [aut, cre] Nicos Pavlidis [aut] |
| Maintainer: | David Hofmeyr <dhofmeyr at sun.ac.za> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | PPCI citation info |
| CRAN checks: | PPCI results |
| Reference manual: | PPCI.pdf |
| Package source: | PPCI_0.1.5.tar.gz |
| Windows binaries: | r-devel: PPCI_0.1.5.zip, r-release: PPCI_0.1.5.zip, r-oldrel: PPCI_0.1.5.zip |
| macOS binaries: | r-release (arm64): PPCI_0.1.5.tgz, r-oldrel (arm64): PPCI_0.1.5.tgz, r-release (x86_64): PPCI_0.1.5.tgz, r-oldrel (x86_64): PPCI_0.1.5.tgz |
| Old sources: | PPCI archive |
| Reverse suggests: | FCPS |
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