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nonet  

Weighted Average Ensemble without Training Labels
View on CRAN: Click here


Download and install nonet package within the R console
Install from CRAN:
install.packages("nonet")

Install from Github:
library("remotes")
install_github("cran/nonet")

Install by package version:
library("remotes")
install_version("nonet", "0.4.0")



Attach the package and use:
library("nonet")
Maintained by
Aviral Vijay
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-12-31
Latest Update: 2019-01-15
Description:
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.
How to cite:
Aviral Vijay (2018). nonet: Weighted Average Ensemble without Training Labels. R package version 0.4.0, https://cran.r-project.org/web/packages/nonet. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.3.0 (2018-12-31 23:20), 0.4.0 (2019-01-15 11:50)
Other packages that cited nonet R package
View nonet citation profile
Other R packages that nonet depends, imports, suggests or enhances
Complete documentation for nonet
Functions, R codes and Examples using the nonet R package
Some associated functions: banknote_authentication . nonet_ensemble . nonet_plot . 
Some associated R codes: nonet_ensemble.R . nonet_plot.R .  Full nonet package functions and examples
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