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ExNRuleEnsemble
View on CRAN: Click
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Download and install ExNRuleEnsemble package within the R console
Install from CRAN:
install.packages("ExNRuleEnsemble")
Install from Github:
library("remotes")
install_github("cran/ExNRuleEnsemble")
Install by package version:
library("remotes")
install_version("ExNRuleEnsemble", "0.1.1")
Attach the package and use:
library("ExNRuleEnsemble")
Maintained by
Amjad Ali
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-14
Latest Update: 2022-12-19
Description:
The extended neighbourhood rule for the k nearest neighbour ensemble where the neighbours are determined in k steps. Starting from the first nearest observation of the test point, the algorithm identifies a single observation that is closest to the observation at the previous step. At each base learner in the ensemble, this search is extended to k steps on a random bootstrap sample with a random subset of features selected from the feature space. The final predicted class of the test point is determined by using a majority vote in the predicted classes given by all base models. Amjad Ali, Muhammad Hamraz, Naz Gul, Dost Muhammad Khan, Saeed Aldahmani, Zardad Khan (2022) .
How to cite:
Amjad Ali (2022). ExNRuleEnsemble: A k Nearest Neibour Ensemble Based on Extended Neighbourhood Rule. R package version 0.1.1, https://cran.r-project.org/web/packages/ExNRuleEnsemble. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2022-12-14 12:50)
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imports, suggests or enhances
Complete documentation for ExNRuleEnsemble
Functions, R codes and Examples using
the ExNRuleEnsemble R package
Some associated functions: ExNRule . ILPD .
Some associated R codes: ExNRule.R . Full ExNRuleEnsemble package functions and examples
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