[2303.12210] A Random Projection k Nearest Neighbours Ensemble for Classification via Extended Neighbourhood Rule
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Statistics > Machine Learning

arXiv:2303.12210 (stat)
[Submitted on 21 Mar 2023]

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

Authors:Amjad Ali, Muhammad Hamraz, Dost Muhammad Khan, Wajdan Deebani, Zardad Khan
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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.
Comments: 23 pages, 8 diagrams, 69 references
Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)
ACM classes: F.2.2
Cite as: arXiv:2303.12210 [stat.ML]
  (or arXiv:2303.12210v1 [stat.ML] for this version)
  https://doi.org/10.48550/arXiv.2303.12210

Submission history

From: Amjad Ali [view email]
[v1] Tue, 21 Mar 2023 21:58:59 UTC (134 KB)
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