A Random Projection k Nearest Neighbours Ensemble for Classification via
Extended Neighbourhood Rule
- URL: http://arxiv.org/abs/2303.12210v1
- Date: Tue, 21 Mar 2023 21:58:59 GMT
- 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
- Abstract summary: Ensembles based on k nearest neighbours (kNN) combine a large number of base learners.
RPExNRule ensemble is proposed where bootstrap samples from the given training data are randomly projected into lower dimensions.
- Score: 0.5052937880533719
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
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