Exploring Social Network Structures Through Friendship-Driven Community Detection with Association Rules Mining


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Documentation for package ‘arlclustering’ version 1.0.5

Help Pages

arlc_calculate_mode Calculate the Mode of a Vector
arlc_clean_final_rules Clean Final Rules
arlc_clusters_plot Plot Graph with Custom Layout and Communities
arlc_convert_date_format Convert a Date to a Different Format
arlc_count_na Count NA Values in a Data Frame
arlc_df_summary Create a Summary of a Data Frame
arlc_fct_clean_transactions Clean Transactions by Removing Overlapping Sets
arlc_fct_get_best_apriori_thresholds Get Best Apriori Thresholds
arlc_file_exists_readable Check if a File Exists and is Readable
arlc_generate_clusters Generate Clusters
arlc_generate_date_sequence Generate a Sequence of Dates
arlc_generate_uid Generate a Unique Identifier
arlc_gen_gross_rules Get Gross Rules
arlc_gen_transactions Get Transactional Dataset
arlc_get_apriori_thresholds Get Apriori Thresholds
arlc_get_network_dataset Get Network Dataset
arlc_get_NonR_rules Get Non-Redundant Rules
arlc_get_significant_rules Get Significant Rules
arlc_is_numeric_vector Check if a Vector is Numeric
arlc_list_to_df Convert List of Vectors to Data Frame
arlc_measure_time Measure Execution Time of a Function
arlc_normalize_vector Normalize a Numeric Vector
arlc_replace_na Replace NA with a Specified Value