An Approach for Machine-Learning Modelling

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 H2O.ai (Oct. 2016). R Interface for H2O, R package version 3.10.0.8. < https://github.com/h2oai/h2o-3>; Zhang W (2016). .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("APML")

0.0.1 by Xinlei Deng, a month ago


Browse source code at https://github.com/cran/APML


Authors: Xinlei Deng [aut, cre, cph] , Wangjian Zhang [aut] , Shao Lin [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports tidyverse, h2o, DMwR, dummies, dplyr, ggplot2, pROC, survival


See at CRAN