get_strength_sim: Determines testing patient class based on the strength of its...

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

Description

Determines testing patient class based on the strength of its similarities with the training patients that populate the two classes in comparison

Usage

get_strength_sim(tepat, m_sim, m_sim_cl, vars_list, top_th = 0.3)

Arguments

tepat	String character of the name of the testing profile
m_sim	Matrix: Original PSN with all the profiles both training and testing
m_sim_cl	Matrix: Clustering PSN of only training profiles
vars_list	Simpati object: List of variables
top_th	Percentage of profiles of each class to compare with testing profile

Value

A dataframe of information for the profile class prediction, precisely: A_strength: how much is WJ similar to A profiles similarities B_strength: how much is WJ similar to B profiles similarities

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