ExNRuleEnsemble
0.1.1A k Nearest Neibour Ensemble Based on Extended Neighbourhood Rule
Overview
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.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Code & Tests
- Cyclomatic complexity
- 5.0 median / 5 max
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1 0 exported
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5 avg / 5 max
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People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.1Latest
- 0.1.02022-12-14
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-12-14
- Total releases
- 2 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 5.8 KB / 1 file
- Download size
- 9.6 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet