Package: SAMGEP 0.1.0-1

Yuri Ahuja

SAMGEP: A Semi-Supervised Method for Prediction of Phenotype Event Times

A novel semi-supervised machine learning algorithm to predict phenotype event times using Electronic Health Record (EHR) data.

Authors:Yuri Ahuja [aut, cre], Tianxi Cai [aut], PARSE LTD [aut]

SAMGEP_0.1.0-1.tar.gz
SAMGEP_0.1.0-1.tar.gz(r-4.7-arm64)SAMGEP_0.1.0-1.tar.gz(r-4.7-x86_64)SAMGEP_0.1.0-1.tar.gz(r-4.6-arm64)SAMGEP_0.1.0-1.tar.gz(r-4.6-x86_64)
SAMGEP_0.1.0-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SAMGEP/json (API)

# Install 'SAMGEP' in R:
install.packages('SAMGEP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/celehs/samgep/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

2.70 score 3 scripts 209 downloads 1 exports 12 dependencies

Last updated from:6a1e1fdad2. Checks:4 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE125
linux-devel-x86_64NOTE136
source / vignettesOK269
linux-release-arm64NOTE124
linux-release-x86_64NOTE125
wasm-releaseOK116

Exports:samgep

Dependencies:abindcodetoolsdoParallelforeachiteratorslatticemvtnormnlmenloptrpROCRcppRcppArmadillo

Simulated Example

Yuri Ahuja

Rendered fromexample.Rmdusingknitr::rmarkdownon Jun 06 2026.

Last update: 2021-01-06
Started: 2021-01-06