A Random Projection k Nearest Neighbours Ensemble for Classification via Extended Neighbourhood Rule

Amjad Ali, Muhammad Hamraz, Dost Muhammad Khan, Wajdan Deebani, Zardad Khan
3/21/2023
stat.MLcs.LG

No confident code implementation found for this paper.

Abstract

Ensembles based on k nearest neighbours (kNN) combine a large number of base learners, each constructed on a sample taken from a given training data. Typical kNN based ensembles determine the k closest observations in the training data bounded to a test sample point by a spherical region to predict its class. In this paper, a novel random projection extended neighbourhood rule (RPExNRule) ensemble is proposed where bootstrap samples from the given training data are randomly projected into lower dimensions for additional randomness in the base models and to preserve features information. It uses the extended neighbourhood rule (ExNRule) to fit kNN as base learners on randomly projected bootstrap samples.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Explaining the Success of Nearest Neighbor Methods in Prediction

79% match2025

Adaptive k-nearest neighbor classifier based on the local estimation of the shape operator

79% match1 repo42024

On high-dimensional modifications of the nearest neighbor classifier

78% match2024

Learning conditional distributions on continuous spaces

77% match1 repo2024

pNNCLR: Stochastic Pseudo Neighborhoods for Contrastive Learning based Unsupervised Representation Learning Problems

77% match2023

A Novel Pseudo Nearest Neighbor Classification Method Using Local Harmonic Mean Distance

77% match2024

Cite this paper

@article{ali2023random,
  title  = {A Random Projection k Nearest Neighbours Ensemble for Classification via Extended Neighbourhood Rule},
  author = {Amjad Ali and Muhammad Hamraz and Dost Muhammad Khan and Wajdan Deebani and Zardad Khan},
  year   = {2023},
  eprint = {2303.12210},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.12210v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2303.12210.svg)](https://codeofpaper.com/paper/2303.12210)

Discussion