clustAnalytics0.5.5 package

Cluster Evaluation on Graphs

conductance

Conductance

contingency_to_membership_vectors

Computes possible membership vectors from contingency table

count_contingency_tables_log

Natural logarithm of the number of contingency tables

coverage

Coverage

cut_ratio

Cut Ratio

density_ratio

Density Ratio

edges_inside

Edges Inside

estimate_H_fraction_r_rows

Estimates |H_0|/|H_r*|

estimate_H_fractions

Estimates |H_i|/|H_{i+1}| for the first r rows

evaluate_significance

Evaluates significance of cluster algorithm results on a graph

apply_subgraphs

Applies function to each subgraph of a graph

auxiliary_functions

Auxiliary Functions of a Graph Partition

average_degree

Average Degree

average_odf

Average Out Degree Fraction

barabasi_albert_blocks

Generates a Barabási-Albert graph with community structure

boot_alg_list

Performs nonparametric bootstrap to a graph and a list of clustering a...

c_rs_table

Contingency table from membership vectors

clustAnalytics-package

clustAnalytics: Cluster Evaluation on Graphs

evaluate_significance_r

Evaluates the significance of a graph's clusters

expansion

Expansion

FOMD

FOMD (Fraction Over Median Degree)

H_fractions_rows

Estimates |H_i|/|H_(i+1)| for the first n_rows rows

igraph_to_edgelist

Returns edgelist with weights from a weighted igraph graph

internal_density

Internal Density

log_omega_estimation

Approximation of log(omega(a,b))

make_graph_weighted

Make graph weighted

max_odf

Max Out Degree Fraction

normalized_cut

Normalized cut

out_degree_fractions

Maximum, Average, and Flake Out Degree Fractions of a Graph Partition

reduced_mutual_information

Reduced Mutual Information

relabel

Relabels membership vector

rewireCpp

Randomizes a weighted graph while keeping the degree distribution cons...

scoring_functions

Scoring Functions of a Graph Partition

sort_matrix

Sort matrix

triangle_participation_ratio_communities

Triangle Participation Ratio (community-wise)

walk_step

Performs a step of the Markov Chain Monte Carlo method

weighted_clustering_coefficient

Weighted clustering coefficient of a weighted graph.

weighted_transitivity

Weighed transitivity of a weighted graph.

Evaluates the stability and significance of clusters on 'igraph' graphs. Supports weighted and unweighted graphs. Implements the cluster evaluation methods defined by Arratia A, Renedo M (2021) <doi:10.7717/peerj-cs.600>. Also includes an implementation of the Reduced Mutual Information introduced by Newman et al. (2020) <doi:10.1103/PhysRevE.101.042304>.

  • Maintainer: Martí Renedo Mirambell
  • License: GPL (>= 3)
  • Last published: 2024-02-18