Perspectives of Machine Learning for Anthropometry Data Processing

Abstract

The most popular machine learning methods with a teacher are linear regression, the method of near neighbors and decision trees. In the course of this work, the most important anthropometric parameters for male skiers were determined through the use of artificial intelligence. The data was evaluated in 3 stages using various machine learning methods. As a result, for male skiers, the most important indicators were shoulder length, elbow diameter, wrist circumference, skin-fat fold of the wrist in front, wrist diameter, shoulder width and frontal diameter of the chest. Thus, we found out that machine learning methods can be used to determine the most important anthropometric parameters for a particular sport.