ExNRuleEnsemble: A k Nearest Neibour Ensemble Based on Extended Neighbourhood
Rule
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>.
Version: |
0.1.1 |
Depends: |
R (≥ 2.10) |
Imports: |
FNN |
Published: |
2022-12-19 |
Author: |
Amjad Ali [aut, cre, cph],
Muhammad Hamraz [aut],
Saeed Aldahmani [aut],
Zardad Khan [aut] |
Maintainer: |
Amjad Ali <Amjad.ali at awkum.edu.pk> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
no |
CRAN checks: |
ExNRuleEnsemble results |
Documentation:
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