It provides ensemble capabilities to supervised and unsupervised learning models predictions without using training labels. It decides the relative weights of the different models predictions by using best models predictions as response variable and rest of the mo. User can decide the best model, therefore, It provides freedom to user to ensemble models based on their design solutions.
Version: 0.4.0 Depends: R (≥ 3.5.0) Imports: caret (≥ 6.0.78), dplyr, randomForest, ggplot2, rlist (≥ 0.4.6.1), glmnet, tidyverse, e1071, purrr, pROC (≥ 1.13.0), rlang (≥ 0.2.1) Suggests: testthat, knitr, rmarkdown, ClusterR Published: 2019-01-15 DOI: 10.32614/CRAN.package.nonet Author: Aviral Vijay [aut, cre], Sameer Mahajan [aut] Maintainer: Aviral Vijay <aviral.vijay at gslab.com> BugReports: https://github.com/GSLabDev/nonet/issues License: MIT + file LICENSE URL: https://open.gslab.com/nonet/ NeedsCompilation: no Materials: README CRAN checks: nonet results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=nonet to link to this page.
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