get_power: Determines the POWER of a patient similarity network
In LucaGiudice/Simpati: Pathway-based classifier exploits patient similarity network paradigm
Description
Usage
Arguments
Value
Description
Computes how much the two classes separate based on their similarity
Usage
1
get_power(m_sim_cl, Aletter, Bletter)
Arguments
m_sim_cl
Similarity matrix
Aletter
Character string. One letter to recognise the first class profiles
Bletter
Character string. One letter to recognise the second class profiles
Value
Return the power (grade of separation between classes) of the similarity matrix
LucaGiudice/Simpati documentation built on Jan. 27, 2022, 11:42 p.m.
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Description Usage Arguments Value
Description
Computes how much the two classes separate based on their similarity
Usage
1 | get_power(m_sim_cl, Aletter, Bletter)
|
Arguments
m_sim_cl |
Similarity matrix |
Aletter |
Character string. One letter to recognise the first class profiles |
Bletter |
Character string. One letter to recognise the second class profiles |
Value
Return the power (grade of separation between classes) of the similarity matrix
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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