Title: Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics

Type Dataset Oscar Miguel-Hurtado, Righard Guest, Sarah V. Stevenage, Greg J. Neil, Sue Black (2016): Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics. Zenodo. Dataset. https://zenodo.org/record/17487

Authors: Oscar Miguel-Hurtado (University of Kent) ; Righard Guest (University of Kent) ; Sarah V. Stevenage (University of Southampton) ; Greg J. Neil (University of Southampton) ; Sue Black (University of Dundee) ;

Links

• Item record in Zenodo
• Digital object URL

Summary

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Data for "Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics" (PLOSONE)

Oscar Miguel-Hurtado1, Richard Guest1, Sarah V. Stevenage2,Greg J. Neil2,Sue Black3  

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For more information please contact: O.Miguel-Hurtado-98@kent.ac.uk (Oscar Miguel)

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The zip contains right and left hand geometry images  from 112 participants. The images were captured using a Nikon D200 SLR camera (format: jpg, size: 3504x2336 pixels), with both the palm of the hand and camera facing downwards. Participants placed each hand on an acetate sheet with a series of positioning pegs.

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The excel contains a series of length measurements (based on the underlying skeleton of the hand) manually extracted (see Figure 1 for details) along with demographic information from the participants: sex (male or female), height (in cm), weight (in kg) and foot size (in UK sizes).

More information

• DOI: 10.5281/zenodo.17487

Subjects

• Biometrics, Forensic, Hand geometry, Dataset, Soft biometrics

Dates

• Publication date: 2016
• Issued: October 19, 2016

Rights

• https://creativecommons.org/licenses/by-nc/4.0/legalcode Creative Commons Attribution Non Commercial 4.0 International
• info:eu-repo/semantics/openAccess Open Access

Format

electronic resource

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