Package: ExNRuleEnsemble 0.1.1

Amjad Ali
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>.
Authors:
ExNRuleEnsemble_0.1.1.tar.gz
ExNRuleEnsemble_0.1.1.zip(r-4.7-any)ExNRuleEnsemble_0.1.1.zip(r-4.6-any)
ExNRuleEnsemble_0.1.1.tar.gz(r-4.7-any)ExNRuleEnsemble_0.1.1.tar.gz(r-4.6-any)
ExNRuleEnsemble_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ExNRuleEnsemble/json (API)
| # Install 'ExNRuleEnsemble' in R: |
| install.packages('ExNRuleEnsemble', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- ILPD - Indian Liver Patient Dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:7de7b4104a. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 97 | ||
| source / vignettes | OK | 182 | ||
| linux-release | OK | 107 | ||
| windows-devel | OK | 79 | ||
| windows-release | OK | 57 | ||
| wasm-release | OK | 118 |
Exports:ExNRule
Dependencies:FNN
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The Extended Neighbourhood Rule for k Nearest Neibour Ensemble | ExNRule |
| Indian Liver Patient Dataset | ILPD |
