Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes

Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes

The adjusted binary classification (ABC) approach was proposed to assure that the binary classification model reaches a particular accuracy level. The present study evaluated the ABC for osteometric sex classification using multiple machine learning (ML) techniques: linear discriminant analysis (LDA...

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Bibliographic Details
Main Authors: MennattAllah Hassan Attia, Marwa A. Kholief, Nancy M. Zaghloul, Ivana Kružić, Šimun Anđelinović, Željana Bašić, Ivan Jerković
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Biology
Subjects:
machine learning algorithms
adjusted binary classification
osteometric sex estimation
optimal training sample size
Online Access:https://www.mdpi.com/2079-7737/11/6/917

Internet

https://www.mdpi.com/2079-7737/11/6/917

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