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Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model

The present study classified and predicted high and low potential archers from a set of bio-physiological variables trained via a machine learning technique namely k-Nearest Neighbour (k-NN). 50 youth archers drawn from various archery programmes completed a one end archery shooting score test. Bi...

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Main Author: Abdullah, Prof. Madya Dr. Mohamad Razali
Format: Book Section
Language:English
Published: Pleiades Publishing 2018
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.unisza.edu.my/3724/1/FH05-FSSG-18-13762.pdf
http://eprints.unisza.edu.my/3724/
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spelling my-unisza-ir.37242022-01-10T03:22:55Z http://eprints.unisza.edu.my/3724/ Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model Abdullah, Prof. Madya Dr. Mohamad Razali TJ Mechanical engineering and machinery The present study classified and predicted high and low potential archers from a set of bio-physiological variables trained via a machine learning technique namely k-Nearest Neighbour (k-NN). 50 youth archers drawn from various archery programmes completed a one end archery shooting score test. Bio-physiological measurements of systolic blood pressure, diastolic blood pressure, resting respiratory rate, resting heart rate and dietary intake were taken. Multiherachical agglomerative cluster analysis was used to cluster the archers based on the variables tested into low, medium and high potential archers. Three different k-NN models namely fine, medium and coarse were trained based on the measured variables. The five-fold cross-validation technique was utilised in the present investigation. It was shown from the present study, that the utilisation of k-NN is non-trivial in the classification of the performance of the archers. © 2018, Springer Nature Singapore Pte Ltd. Pleiades Publishing 2018 Book Section NonPeerReviewed text en http://eprints.unisza.edu.my/3724/1/FH05-FSSG-18-13762.pdf Abdullah, Prof. Madya Dr. Mohamad Razali (2018) Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model. In: Lecture Notes in Mechanical Engineering. Pleiades Publishing, pp. 377-384. ISBN 21954356
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Abdullah, Prof. Madya Dr. Mohamad Razali
Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
description The present study classified and predicted high and low potential archers from a set of bio-physiological variables trained via a machine learning technique namely k-Nearest Neighbour (k-NN). 50 youth archers drawn from various archery programmes completed a one end archery shooting score test. Bio-physiological measurements of systolic blood pressure, diastolic blood pressure, resting respiratory rate, resting heart rate and dietary intake were taken. Multiherachical agglomerative cluster analysis was used to cluster the archers based on the variables tested into low, medium and high potential archers. Three different k-NN models namely fine, medium and coarse were trained based on the measured variables. The five-fold cross-validation technique was utilised in the present investigation. It was shown from the present study, that the utilisation of k-NN is non-trivial in the classification of the performance of the archers. © 2018, Springer Nature Singapore Pte Ltd.
format Book Section
author Abdullah, Prof. Madya Dr. Mohamad Razali
author_facet Abdullah, Prof. Madya Dr. Mohamad Razali
author_sort Abdullah, Prof. Madya Dr. Mohamad Razali
title Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
title_short Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
title_full Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
title_fullStr Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
title_full_unstemmed Classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
title_sort classification of high performance archers by means of bio-physiological performance variables via k-nearest neighbour classification model
publisher Pleiades Publishing
publishDate 2018
url http://eprints.unisza.edu.my/3724/1/FH05-FSSG-18-13762.pdf
http://eprints.unisza.edu.my/3724/
_version_ 1724079286179069952
score 13.211869

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