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highMLR
View on CRAN: Click
here
Download and install highMLR package within the R console
Install from CRAN:
install.packages("highMLR")
Install from Github:
library("remotes")
install_github("cran/highMLR")
Install by package version:
library("remotes")
install_version("highMLR", "0.1.1")
Attach the package and use:
library("highMLR")
Maintained by
Atanu Bhattacharjee
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-11
Latest Update: 2022-07-18
Description:
Perform high dimensional Feature Selection in the presence of survival outcome.
Based on Feature Selection method and different survival analysis, it will obtain the best
markers with optimal threshold levels according to their effect on disease progression
and produce the most consistent level according to those threshold values.
The functions' methodology is based on by Sonabend et al (2021) and Bhattacharjee et al (2021) .
How to cite:
Atanu Bhattacharjee (2021). highMLR: Feature Selection for High Dimensional Survival Data. R package version 0.1.1, https://cran.r-project.org/web/packages/highMLR
Previous versions and publish date:
0.1.0 (2021-05-11 11:40)
Other packages that cited highMLR R package
View highMLR citation profile
Other R packages that highMLR depends,
imports, suggests or enhances
Functions, R codes and Examples using
the highMLR R package
Some associated functions: hnscc . mlclassCox . mlclassKap . mlhighCox . mlhighFrail . mlhighHet . mlhighKap . srdata .
Some associated R codes: hnscc.R . mlclassCox.R . mlclassKap.R . mlhighCox.R . mlhighFrail.R . mlhighHet.R . mlhighKap.R . srdata.R . Full highMLR package functions and examples
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