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]

naspaclust_0.2.1.tar.gz
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naspaclust_0.2.1.tgz(r-4.5-any)naspaclust_0.2.1.tgz(r-4.4-any)naspaclust_0.2.1.tgz(r-4.3-any)
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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'))

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

Datasets:

On CRAN:

2.00 score 709 downloads 9 exports 8 dependencies

Last updated 4 years agofrom:e2680bbcbc. Checks:1 OK, 7 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 03 2025
R-4.5-winWARNINGFeb 03 2025
R-4.5-macWARNINGFeb 03 2025
R-4.5-linuxWARNINGFeb 03 2025
R-4.4-winWARNINGFeb 03 2025
R-4.4-macWARNINGFeb 03 2025
R-4.3-winWARNINGFeb 03 2025
R-4.3-macWARNINGFeb 03 2025

Exports:abcfgwcfgwcfgwcuvfpafgwcgsafgwchhofgwcifafgwcpsofgwctlbofgwc

Dependencies:audiobeeprrbibutilsRcppRcppArmadillordistRdpackstabledist