Package: Clustering 1.7.10

Clustering: Techniques for Evaluating Clustering

The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided. See Martos, L.A.P., García-Vico, Á.M., González, P. et al.(2023) <doi:10.1007/s13748-022-00294-2> "Clustering: an R library to facilitate the analysis and comparison of cluster algorithms.", Martos, L.A.P., García-Vico, Á.M., González, P. et al. "A Multiclustering Evolutionary Hyperrectangle-Based Algorithm" <doi:10.1007/s44196-023-00341-3> and L.A.P., García-Vico, Á.M., González, P. et al. "An Evolutionary Fuzzy System for Multiclustering in Data Streaming" <doi:10.1016/j.procs.2023.12.058>.

Authors:Luis Alfonso Perez Martos [aut, cre]

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Clustering.pdf |Clustering.html✨
Clustering/json (API)

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

Peer review:

Bug tracker:https://github.com/laperez/clustering/issues

Datasets:
  • basketball - This data set contains a series of statistics (5 attributes) about 96 basketball players:
  • bolts - Data from an experiment on the affects of machine adjustments on the time to count bolts.
  • stock - The data provided are daily stock prices from January 1988 through October 1991, for ten aerospace companies.
  • stulong - The study was performed at the 2nd Department of Medicine, 1st Faculty of Medicine of Charles University and Charles University Hospital. The data were transferred to electronic form by the European Centre of Medical Informatics, Statisticsand Epidemiology of Charles University and Academy of Sciences.
  • weather - One of the most known testing data sets in machine learning. This data sets describes several situations where the weather is suitable or not to play sports, depending on the current outlook, temperature, humidity and wind.

On CRAN:

3.90 score 4 stars 7 scripts 922 downloads 65 mentions 13 exports 95 dependencies

Last updated 7 months agofrom:c6acacce9f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winOKNov 19 2024
R-4.5-linuxOKNov 19 2024
R-4.4-winOKNov 19 2024
R-4.4-macOKNov 19 2024
R-4.3-winOKNov 19 2024
R-4.3-macOKNov 19 2024

Exports:appClusteringbest_ranked_external_metricsbest_ranked_internal_metricsclusteringevaluate_best_validation_external_by_metricsevaluate_best_validation_internal_by_metricsevaluate_validation_external_by_metricsevaluate_validation_internal_by_metricsexport_file_externalexport_file_internalplot_clusteringresult_external_algorithm_by_metricresult_internal_algorithm_by_metric

Dependencies:amapapclusterbase64encbitbit64blobbriobslibcachemcallrchroncliclusterClusterRcodetoolscolorspacecommonmarkcpp11crayondata.tableDBIdescdiffobjdigestdplyrevaluatefansifarverfastmapfontawesomeforeachfsfuturegenericsggplot2globalsgluegmpgsubfngtablehtmltoolshttpuvisobanditeratorsjquerylibjsonlitelabelinglaterlatticelifecyclelistenvmagrittrMASSMatrixmemoisemgcvmimemunsellnlmeparallellypillarpkgbuildpkgconfigpkgloadplogrpracmapraiseprocessxpromisesprotopspvclustR6rappdirsRColorBrewerRcppRcppArmadillorlangrprojrootRSQLitesassscalesshinysourcetoolssqldftestthattibbletidyselecttoOrdinalutf8vctrsviridisLitewaldowithrxtable

Readme and manuals

Help Manual

Help pageTopics
Filter metrics in a 'clustering' object returning a new 'clustering' object.[.clustering
Clustering GUI.appClustering
This data set contains a series of statistics (5 attributes) about 96 basketball players:basketball
Best rated external metrics.best_ranked_external_metrics
Best rated internal metrics.best_ranked_internal_metrics
Data from an experiment on the affects of machine adjustments on the time to count bolts.bolts
Clustering algorithm.clustering
Method to convert columns to ordinal.convert_toOrdinal
Evaluates algorithms by measures of dissimilarity based on a metric.evaluate_best_validation_external_by_metrics
Evaluates algorithms by measures of dissimilarity based on a metric.evaluate_best_validation_internal_by_metrics
Evaluate external validations by algorithm.evaluate_validation_external_by_metrics
Evaluate internal validations by algorithm.evaluate_validation_internal_by_metrics
Export result of external metrics in latex.export_file_external
Export result of internal metrics in latex.export_file_internal
Graphic representation of the evaluation measures.plot_clustering
External results by algorithm.result_external_algorithm_by_metric
Internal results by algorithmresult_internal_algorithm_by_metric
Returns the clustering result sorted by a set of metrics.sort.clustering
The data provided are daily stock prices from January 1988 through October 1991, for ten aerospace companies.stock
The study was performed at the 2nd Department of Medicine, 1st Faculty of Medicine of Charles University and Charles University Hospital. The data were transferred to electronic form by the European Centre of Medical Informatics, Statisticsand Epidemiology of Charles University and Academy of Sciences.stulong
Method for filtering external columns of a dataset.transform_dataset
Method for filtering internal columns of a dataset.transform_dataset_internal
One of the most known testing data sets in machine learning. This data sets describes several situations where the weather is suitable or not to play sports, depending on the current outlook, temperature, humidity and wind.weather