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:
naspaclust_0.2.1.tar.gz
naspaclust_0.2.1.zip(r-4.5)naspaclust_0.2.1.zip(r-4.4)naspaclust_0.2.1.zip(r-4.3)
naspaclust_0.2.1.tgz(r-4.4-any)naspaclust_0.2.1.tgz(r-4.3-any)
naspaclust_0.2.1.tar.gz(r-4.5-noble)naspaclust_0.2.1.tar.gz(r-4.4-noble)
naspaclust_0.2.1.tgz(r-4.4-emscripten)naspaclust_0.2.1.tgz(r-4.3-emscripten)
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
- census2010 - Indonesia 2010 Provincial Census data
- census2010dist - Indonesia Provincial Matrix Distance
- census2010pop - Indonesia 2010 Population
Last updated 3 years agofrom:e2680bbcbc. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
R-4.5-win | WARNING | Nov 05 2024 |
R-4.5-linux | WARNING | Nov 05 2024 |
R-4.4-win | WARNING | Nov 05 2024 |
R-4.4-mac | WARNING | Nov 05 2024 |
R-4.3-win | WARNING | Nov 05 2024 |
R-4.3-mac | WARNING | Nov 05 2024 |
Exports:abcfgwcfgwcfgwcuvfpafgwcgsafgwchhofgwcifafgwcpsofgwctlbofgwc
Dependencies:audiobeeprrbibutilsRcppRcppArmadillordistRdpackstabledist