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    STUDIA INFORMATICA - Issue no. 2 / 2015  

Authors:  .
  Abstract:   In this paper we apply Support Vector Machines to the problem of predicting the height of human skeletons given bone measurements.There exist archaeological methods for estimating height, but our purposeis to investigate the potential of Support Vector Regression for this task. Since skeletal stature clearly depends on individual bone lengths, building SVM models for this task has the potential of giving an accurate machine learning automation for this task, which can be useful for archaeologists.We investigate multiple kernels and performance evaluation methodologies and compare our results to existing literature results on the topic. Our experiments show that SVM regression models are very good for the problemat hand, out performing existing approaches.

2010 Mathematics Subject Classi fication. 68T05, 68T01.
Key words and phrases. height estimation, regression, support vector machines, archaeology, forensic science.
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