Package: APML
Type: Package
Title: An Approach for Machine-Learning Modelling
Version: 0.0.4
Authors@R: c(person("Xinlei","Deng",role=c("aut","cre","cph"),email="xdeng3@albany.edu"),
			 person("Wangjian","Zhang",role="aut"),
			 person("Tianyue","Mi",role="aut"),
			 person("Shao","Lin",role="aut"))
Description: We include
            1) data cleaning including variable scaling, missing values and unbalanced variables identification and removing, and strategies for variable balance improving; 
			2) modeling based on random forest and gradient boosted model including feature selection, model training, cross-validation and external testing.
			For more information, please see Deng X (2021). <doi:10.1016/j.scitotenv.2020.144746>; H2O.ai (Oct. 2016). R Interface for H2O, R package version 3.10.0.8. <https://github.com/h2oai/h2o-3>; Zhang W (2016). <doi:10.1016/j.scitotenv.2016.02.023>.
License: GPL-3
Encoding: UTF-8
Imports: survival,h2o,performanceEstimation,dummies,dplyr,ggplot2,pROC
NeedsCompilation: no
Author: Xinlei Deng [aut, cre, cph],
  Wangjian Zhang [aut],
  Tianyue Mi [aut],
  Shao Lin [aut]
Maintainer: Xinlei Deng <xdeng3@albany.edu>
Repository: CRAN
Packaged: 2022-01-21 03:01:01 UTC; Xinlei Deng
Date/Publication: 2022-01-21 15:32:46 UTC
Built: R 4.0.5; ; 2022-01-25 05:33:04 UTC; unix
