A k Nearest Neibour Ensemble Based on Extended Neighbourhood Rule R package ExNRuleEnsemble version 0.1.1 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) <doi:10.48550/arXiv.2205.15111>. Software Depends: R (>= 2.10) Imports: FNN Amjad Ali <Amjad.ali@awkum.edu.pk> Comprehensive R Archive Network (CRAN) Amjad Ali [aut, cre, cph], Muhammad Hamraz [aut], Saeed Aldahmani [aut], Zardad Khan [aut] GPL (>= 3) 2022-12-19 application/tgz https://CRAN.R-project.org/package=ExNRuleEnsemble doi:10.32614/CRAN.package.ExNRuleEnsemble