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Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics
Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We asses...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091918/ https://www.ncbi.nlm.nih.gov/pubmed/27806075 http://dx.doi.org/10.1371/journal.pone.0165521 |
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author | Miguel-Hurtado, Oscar Guest, Richard Stevenage, Sarah V. Neil, Greg J. Black, Sue |
author_facet | Miguel-Hurtado, Oscar Guest, Richard Stevenage, Sarah V. Neil, Greg J. Black, Sue |
author_sort | Miguel-Hurtado, Oscar |
collection | PubMed |
description | Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. |
format | Online Article Text |
id | pubmed-5091918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50919182016-11-15 Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics Miguel-Hurtado, Oscar Guest, Richard Stevenage, Sarah V. Neil, Greg J. Black, Sue PLoS One Research Article Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. Public Library of Science 2016-11-02 /pmc/articles/PMC5091918/ /pubmed/27806075 http://dx.doi.org/10.1371/journal.pone.0165521 Text en © 2016 Miguel-Hurtado et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Miguel-Hurtado, Oscar Guest, Richard Stevenage, Sarah V. Neil, Greg J. Black, Sue Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title | Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title_full | Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title_fullStr | Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title_full_unstemmed | Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title_short | Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics |
title_sort | comparing machine learning classifiers and linear/logistic regression to explore the relationship between hand dimensions and demographic characteristics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5091918/ https://www.ncbi.nlm.nih.gov/pubmed/27806075 http://dx.doi.org/10.1371/journal.pone.0165521 |
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