Package: naspaclust 0.2.1

naspaclust: Nature-Inspired Spatial Clustering

Implement and enhance the performance of spatial fuzzy clustering using Fuzzy Geographically Weighted Clustering with various optimization algorithms, mainly from Xin She Yang (2014) <ISBN:9780124167438> with book entitled Nature-Inspired Optimization Algorithms. The optimization algorithm is useful to tackle the disadvantages of clustering inconsistency when using the traditional approach. The distance measurements option is also provided in order to increase the quality of clustering results. The Fuzzy Geographically Weighted Clustering with nature inspired optimisation algorithm was firstly developed by Arie Wahyu Wijayanto and Ayu Purwarianti (2014) <doi:10.1109/CITSM.2014.7042178> using Artificial Bee Colony algorithm.

Authors:Bahrul Ilmi Nasution [aut, cre], Robert Kurniawan [aut], Rezzy Eko Caraka [aut]

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naspaclust.pdf |naspaclust.html
naspaclust/json (API)

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

Peer review:

Bug tracker:https://github.com/bmlmcmc/naspaclust/issues

Datasets:

On CRAN:

2.00 score 654 downloads 9 exports 8 dependencies

Last updated 3 years agofrom:e2680bbcbc. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winWARNINGNov 05 2024
R-4.5-linuxWARNINGNov 05 2024
R-4.4-winWARNINGNov 05 2024
R-4.4-macWARNINGNov 05 2024
R-4.3-winWARNINGNov 05 2024
R-4.3-macWARNINGNov 05 2024

Exports:abcfgwcfgwcfgwcuvfpafgwcgsafgwchhofgwcifafgwcpsofgwctlbofgwc

Dependencies:audiobeeprrbibutilsRcppRcppArmadillordistRdpackstabledist