Nominal Data Mining Analysis
General properties of the network
Extract the non-missing submatrices from a given matrix.
Find clusters in projected unipartite networks
NIMAA: A package for Nominal Data Mining Analysis.
Convert nominal data to a bipartite network
Plot the bipartite network and the corresponding projected networks
Use the incidence matrix to plot an interactive bipartite network
Plot the clusters in one projection of the bipartite network
Plot the incidence matrix.
Edge prediction of weighted bipartite network.
Score the cluster analysis in a projected network based on additional ...
Validate the cluster analysis in a projected network based on addition...
Validate and compare edge prediction methods.
Plot the bipartite graph with color coding for different clusters in b...
Functions for nominal data mining based on bipartite graphs, which build a pipeline for analysis and missing values imputation. Methods are mainly from the paper: Jafari, Mohieddin, et al. (2021) <doi:10.1101/2021.03.18.436040>, some new ones are also included.