Easily Build and Evaluate Machine Learning Models

Easily build and evaluate machine learning models on a dataset. Machine learning models supported include penalized linear models, penalized linear models with interactions, random forest, support vector machines, neural networks, and deep neural networks.


Reference manual

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


0.1.0 by Woo-Young Ahn, a year ago


Report a bug at https://github.com/CCS-Lab/easyml/issues

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

Authors: Woo-Young Ahn [aut, cre], Paul Hendricks [aut], OSU-CCSL [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports caret, corrplot, darch, dummies, e1071, futile.logger, ggplot2, glinternet, glmnet, parallel, pbapply, pbmcapply, pROC, nnet, randomForest, scales, scorer

Suggests covr, lintr, testthat, knitr, rmarkdown

See at CRAN