CRAN

nonet 0.4.0

Weighted Average Ensemble without Training Labels

Released Jan 15, 2019 by Aviral Vijay

This package cannot yet be used with Renjin it depends on other packages which are not available: dplyr 0.7.8, ggplot2 3.1.0, caret 6.0-81, tidyverse 1.2.1, and rlang 0.3.1

Dependencies

tidyverse 1.2.1 rlang 0.3.1 ggplot2 3.1.0 caret 6.0-81 dplyr 0.7.8 rlist 0.4.6.1 glmnet 2.0-16 pROC 1.13.0 randomForest 4.6-14 e1071 1.7-0 purrr 0.2.5

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.

Source

R

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