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

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0.1.0 by Woo-Young Ahn, 3 months 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