Package: PPCI 0.1.5

David Hofmeyr

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>.

Authors:David Hofmeyr <[email protected]> [aut, cre] Nicos Pavlidis <[email protected]> [aut]

PPCI_0.1.5.tar.gz
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PPCI.pdf |PPCI.html
PPCI/json (API)

# Install 'PPCI' in R:
install.packages('PPCI', repos = c('https://davidhofmeyr.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/davidhofmeyr/ppci/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • breastcancer - Discrimination of Cancerous and Non-Cancerous Breast Masses
  • dermatology - Eryhemato-Squamous Disease Identification
  • optidigits - Optical Recognition of Handwritten Digits
  • pendigits - Pen-based Recognition of Handwritten Digits
  • phoneme - Speech Recognition through Phoneme Identification
  • yale - Face Recognition

On CRAN:

3.26 score 2 stars 18 scripts 163 downloads 44 exports 7 dependencies

Last updated 5 years agofrom:aa8fa12f6c. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 14 2024
R-4.5-win-x86_64WARNINGOct 14 2024
R-4.5-linux-x86_64WARNINGOct 14 2024
R-4.4-win-x86_64WARNINGOct 14 2024
R-4.4-mac-x86_64WARNINGOct 14 2024
R-4.4-mac-aarch64WARNINGOct 14 2024
R-4.3-win-x86_64WARNINGOct 14 2024
R-4.3-mac-x86_64WARNINGOct 14 2024
R-4.3-mac-aarch64WARNINGOct 14 2024

Exports:add_subtreecluster_performancedf_mcdf_mddf_md_cppdf_ncutdncut_xf_mcf_mdf_md_cppf_ncuthp_plotis_minimismin_cppmc_bmcdcmcdrmchmcppmd_bmd_b_cppmd_reldepthmddcmddrmdhmdppncut_bncut_xncutdcncutdrncuthncutppnode_plotnorm_vecoptidigits_mean_imagesplot.ppci_cluster_solutionplot.ppci_hyperplane_solutionplot.ppci_projection_solutionppclust.optimsubtree_widthsuccess_ratiotree_plottree_prunetree_split

Dependencies:latticeMatrixrARPACKRcppRcppArmadilloRcppEigenRSpectra