{"text_format":"2","workbook":"xlsx","n_sheets":1,"sheets":["S5 Table"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":0,"defined_names":0,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900"}

{"sheet":"S5 Table","index":0,"n_rows":15,"n_cols":3,"rows_kept":15,"cut":false,"hidden":false,"merged":[[0,0,0,2]]}
["S5 Table. Optimisation metrics used on base algorithms. List of metrics used to optimise the base partitions for different algorithms, where required. Popular metrics commonly associated to a given algorithm that are known to give the best performance were prioritised. When such was not available, modularity maximisation was used."]
["Clustering algorithm","Optimised parameter/Model choice","Optimisation metric"]
["k-means","Input number of clusters","Modularity"]
["Hierarchical (average link.)","Dendrogram cut (number of clusters)","Modularity"]
["Fuzzy C-means","Membership matrix (U)","FCP"]
["Model-based clustering","Best fitted model","BIC"]
["MCL","Expansion and inflation","Modularity"]
["Density-based clustering","NA","NA"]
["Edge betweenness","Dendrogram cut (number of clusters)","Modularity"]
["Louvain","NA","NA"]
["Leading eigenvector","Dendrogram cut (number of clusters)","Modularity"]
["Fast greedy","Dendrogram cut (number of clusters)","Modularity"]
["Lapel propagation","NA","NA"]
["Walktrap","Dendrogram cut (number of clusters)","Modularity"]
["InfoMap","NA","NA"]