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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling source/ R- | ExNRuleEnsemble_0.1.1.tar.gz |
9.6 KiB |
0.1.1 |
latest source/ R- | ExNRuleEnsemble_0.1.1.tar.gz |
9.6 KiB |
0.1.1 |
2026-04-23 source/ R- | ExNRuleEnsemble_0.1.1.tar.gz |
9.6 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | ExNRuleEnsemble_0.1.1.zip |
27.9 KiB |