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Clustering  

Techniques for Evaluating Clustering
View on CRAN: Click here


Download and install Clustering package within the R console
Install from CRAN:
install.packages("Clustering")

Install from Github:
library("remotes")
install_github("cran/Clustering")

Install by package version:
library("remotes")
install_version("Clustering", "1.7.10")



Attach the package and use:
library("Clustering")
Maintained by
Luis Alfonso Perez Martos
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-31
Latest Update: 2022-06-22
Description:
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.
How to cite:
Luis Alfonso Perez Martos (2020). Clustering: Techniques for Evaluating Clustering. R package version 1.7.10, https://cran.r-project.org/web/packages/Clustering. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2020-03-31 11:50), 1.1 (2020-04-05 02:00), 1.2 (2020-04-11 16:30), 1.3 (2020-04-16 11:00), 1.4 (2020-04-17 12:00), 1.5 (2020-04-22 00:00), 1.6 (2020-04-23 18:10), 1.7.1 (2020-12-04 19:30), 1.7.2 (2021-01-07 11:30), 1.7.3 (2021-09-22 21:30), 1.7.4 (2021-12-08 20:30), 1.7.5 (2021-12-14 14:50), 1.7.6 (2022-04-19 20:02), 1.7.7 (2022-06-22 11:40), 1.7 (2020-10-25 18:50)
Other packages that cited Clustering R package
View Clustering citation profile
Other R packages that Clustering depends, imports, suggests or enhances
Complete documentation for Clustering
Functions, R codes and Examples using the Clustering R package
Some associated functions: aggExCluster_euclidean . agnes_euclidean_method . agnes_manhattan_method . algorithm_amap . algorithm_apcluster . algorithm_cluster . algorithm_clusterr . algorithm_pvclust . algorithms . algorithms_package . apclusterK_euclidean . apclusterK_manhattan . apclusterK_minkowski . appClustering . basketball . best_ranked_external_metrics . best_ranked_internal_metrics . bolts . calculate_best_external_variables_by_metrics . calculate_best_internal_variables_by_metrics . calculate_best_validation_external_by_metrics . calculate_best_validation_internal_by_metrics . calculate_connectivity . calculate_dunn . calculate_result . calculate_result_internal . calculate_validation_external_by_metrics . calculate_validation_internal_by_metrics . clara_euclidean_method . clara_manhattan_method . clustering . connectivity_metric . convert_numeric_matrix . convert_table . convert_toOrdinal . daisy_euclidean_method . daisy_gower_method . daisy_manhattan_method . dataframe_by_metrics_evaluation . detect_definition_attribute . diana_euclidean_method . dunn_metric . entropy_formula . entropy_metric . evaluate_all_column_dataset . evaluate_best_validation_external_by_metrics . evaluate_best_validation_internal_by_metrics . evaluate_validation_external_by_metrics . evaluate_validation_internal_by_metrics . execute_datasets . execute_package_parallel . export_file_external . export_file_internal . extension_file . external_validation . fanny_euclidean_method . fanny_manhattan_method . fill_cluster_vector . fmeasure_metric . fowlkes_mallows_index_metric . gmm_euclidean_method . gmm_manhattan_method . hclust_euclidean . information_external . information_internal . initializeExternalValidation . initializeInternalValidation . internal_validation . is_External_Metrics . is_Internal_Metrics . kmeans_arma_method . kmeans_rcpp_method . max_value_metric . measure_amap . measure_apcluster . measure_calculate . measure_cluster . measure_clusterr . measure_package . measure_pvclust . metrics_calculate . metrics_external . metrics_internal . metrics_validate . mini_kmeans_method . mona_method . number_columnas_external . number_columnas_internal . number_variables_dataset . packages . pam_euclidean_method . pam_manhattan_method . path_dataset . plot_clustering . precision_metric . pvclust_correlation_method . pvclust_euclidean_method . pvpick_method . read_file . recall_metric . refactorName . resultClustering . result_external_algorithm_by_metric . result_internal_algorithm_by_metric . row_name_df_external . row_name_df_internal . show_result_external_algorithm_by_metric . show_result_external_algorithm_group_by_clustering . show_result_internal_algorithm_by_metric . show_result_internal_algorithm_group_by_clustering . silhouette_metric . sort.clustering . specify_decimal . stock . stulong . sub-.clustering . transform_dataset . transform_dataset_internal . variation_information_metric . weather . 
Some associated R codes: aggExCluster.R . agnes.R . algorithm.R . apcluster.R . app.R . basketball-data.R . bolts-data.R . clara.R . constants.R . daisy.R . diana.R . evaluate_column_dataset.R . external_validation.R . fanny.R . gmm.R . hclust.R . internal_validation.R . kmeans.R . mona.R . pam.R . pvclust.R . pvpick.R . read_arff.R . stock-data.R . stulong-data.R . utils.R . validation.R . weather-data.R .  Full Clustering package functions and examples
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