Package: geocmeans 0.3.4

Jeremy Gelb

geocmeans: Implementing Methods for Spatial Fuzzy Unsupervised Classification

Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed. The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).

Authors:Jeremy Gelb [aut, cre], Philippe Apparicio [ctb]

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geocmeans.pdf |geocmeans.html✨
geocmeans/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/jeremygelb/geocmeans/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • LyonIris - Social and environmental indicators for the Iris of the metropolitan region of Lyon

On CRAN:

clusteringcmeansfuzzy-classification-algorithmsspatial-analysisspatial-fuzzy-cmeansunsupervised-learning

116 exports 27 stars 2.40 score 149 dependencies 50 scripts 373 downloads

Last updated 12 months agofrom:4dd7cd189f. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-win-x86_64OKSep 14 2024
R-4.5-linux-x86_64OKSep 14 2024
R-4.4-win-x86_64OKSep 14 2024
R-4.4-mac-x86_64OKSep 14 2024
R-4.4-mac-aarch64OKSep 14 2024
R-4.3-win-x86_64OKSep 14 2024
R-4.3-mac-x86_64OKSep 14 2024
R-4.3-mac-aarch64OKSep 14 2024

Exports:add_matrices_bycoladj_spconsist_arr_window_globstdadjustSpatialWeightsbarPlotsbelongsFCMbelongsGFCMbelongsSFCMbelongsSGFCMboot_group_validationboot_group_validation.mcboot_workercalc_jaccard_idxcalc_jaccard_matcalc_local_moran_rastercalc_moran_rastercalc_raster_spinconsistencycalcBelongMatrixcalcBelongMatrixNoisycalcCalinskiHarabaszcalcCentroidscalcDaviesBouldincalcELSAcalcEuclideanDistancecalcEuclideanDistance2calcEuclideanDistance3calcexplainedInertiacalcFGCMBelongMatrixcalcFGCMBelongMatrixNoisycalcFukuyamaSugenocalcFuzzyELSAcalcFuzzyElsa_rastercalcGD43calcGD53calcLaggedDatacalcNegentropyIcalcQualIdxcalcqualityIndexescalcRobustSigmascalcSFCMBelongMatrixcalcSFCMBelongMatrixNoisycalcSFGCMBelongMatrixcalcSFGCMBelongMatrixNoisycalcSilhouetteIdxcalcSWFCCentroidscalcUncertaintyIndexcalcWdataRastercat_to_belongingscatToBelongingscentersFCMcentersGFCMcentersSFCMcentersSGFCMcheck_matdistcheck_raters_dimscheck_windowcircular_windowCMeansdiv_matrices_bycolElsa_categorical_matrix_windowElsa_fuzzy_matrix_windowelsa_fuzzy_vectorelsa_rasterelsa_vectoreval_parametersevaluateMatricesFCMresfocal_adj_mean_arr_windowfocal_euclidean_arr_windowfocal_euclidean_listfocal_euclidean_mat_windowGCMeansgeocmeans_envgroups_matchinginput_raster_datais.FCMreskppCentersload_arcachonlocal_moranI_matrix_windowmain_workermapClustersmapRastersmapThismax_matmoranI_matrix_windowoutput_raster_dataplot.FCMrespow_matrix_bycolpower_matpredict_membershippredict.FCMresprint.FCMresprod_matrices_bycolrowmins_matsanity_checkselect_parametersselect_parameters.mcselectParametersselectParameters.mcSFCMeansSGFCMeanssp_clust_explorerspatialDiagspConsistencyspiderPlotssqrt_matrix_bycolstandardizersub_matrices_bycolsummarizeClusterssummary.FCMrestest_inferior_matuncertaintyMapundecidedUnitsvecmaxvecminvector_out_prodviolinPlots

Dependencies:abindaskpassbackportsbase64encBHbootbslibcachemcallrcheckmateclassclassIntclicodetoolscolorspacecommonmarkcpp11crayoncrosstalkcurldata.tableDBIdeldirdensEstBayesdescdichromatdigestdistributionaldplyre1071evaluatefansifarverfastmapfclustfmsbfontawesomefsfuturefuture.applygenericsgeojsonsfgeometriesggplot2globalsgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrinlineisobandjquerylibjsonifyjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleafemleafletleaflet.providersleafsynclifecyclelistenvloolwgeommagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmenumDerivopensslparallellypillarpkgbuildpkgconfigplotlyplyrpngposteriorprocessxprogressrpromisesproxypspurrrQuickJSRR6rapidjsonrrappdirsrasterrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreldistreshape2rlangrmarkdownrstanrstantoolss2sassscalessfsfheadersshinysourcetoolsspspDataspdepStanHeadersstarsstringistringrsystensorAterratibbletidyrtidyselecttinytextmaptmaptoolsunitsutf8vctrsviridisLitewidgetframewithrwkxfunXMLxtableyaml

Spatial Fuzzy CMean with R

Jeremy Gelb

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-09-12
Started: 2020-03-21

Readme and manuals

Help Manual

Help pageTopics
Semantic adjusted spatial weightsadjustSpatialWeights
SpatRaster of the bay of ArcachonArcachon load_arcachon
Bar plotsbarPlots
Check the robustness of a classification by Bootstrapboot_group_validation
Check that the obtained groups are stable by bootstrap (multicore)boot_group_validation.mc
Local Moran I for rastercalc_local_moran_raster
Global Moran I for rastercalc_moran_raster
Calinski-Harabasz indexcalcCalinskiHarabasz
Davies-Bouldin indexcalcDaviesBouldin
calculate ELSA statistic for a hard partitioncalcELSA
Explained inertia indexcalcexplainedInertia
Fukuyama and Sugeno indexcalcFukuyamaSugeno
calculate ELSA statistic for a fuzzy partitioncalcFuzzyELSA
Generalized Dunn’s index (43)calcGD43
Generalized Dunn’s index (53)calcGD53
Negentropy Increment indexcalcNegentropyI
Quality indexescalcqualityIndexes
Fuzzy Silhouette indexcalcSilhouetteIdx
Diversity indexcalcUncertaintyIndex
Convert categories to membership matrixcatToBelongings cat_to_belongings
Circular windowcircular_window
C-meansCMeans
Generalized C-meansGCMeans
Match the groups obtained from two classificationsgroups_matching
is method for FCMresis.FCMres
social and environmental indicators for the Iris of the metropolitan region of Lyon (France)LyonIris
Mapping the clustersmapClusters
Plot method for FCMres objectplot.FCMres
Predict matrix membership for new observationspredict_membership
Predict method for FCMres objectpredict.FCMres
print method for FCMresprint.FCMres
Select parameters for a clustering algorithmselectParameters select_parameters
Select parameters for clustering algorithm (multicore)selectParameters.mc select_parameters.mc
SFCMeansSFCMeans
SGFCMeansSGFCMeans
Classification result explorersp_clust_explorer
Spatial diagnosticspatialDiag
Spatial consistency indexspConsistency
Spider chartspiderPlots
Standardizing helperstandardizer
Descriptive statistics by groupsummarizeClusters
Summary method for FCMressummary.FCMres
Uncertainty mapuncertaintyMap
Undecided observationsundecidedUnits
Violin plotsviolinPlots