strong.comm.AA.cor: Calls the BFC algorithm over the first patient class...

In LucaGiudice/Simpati: Pathway-based classifier exploits patient similarity network paradigm

Description

Calls the BFC algorithm over the first patient class correcting the values of the input patient similarity networks

Usage

strong.comm.AA.cor(mat, nAs, thW = 0.6, thGroup = 0.6, strong = T)

Arguments

mat	adjacency matrix of a patient similarity network
nAs	number of patients composing the first class
thW	Default 0.6, double value between 0 and 1 determining the percentage of best friends to considers for a root (1BFS are the 60 percentage of the patients most similar to the root)
thGroup	Default 0.6, double value between 0 and 1 determining the percentage of best friends to keep in the end as final subclass
strong	Default TRUE, if the first class is signature class of the PSN passed as matrix (mat)

Value

filtered input PSN without the patients that have not been considered representatives of their own class

LucaGiudice/Simpati documentation built on Jan. 27, 2022, 11:42 p.m.