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A fuzzy decision tree based method for skeletal sex determination

机译:基于模糊决策树的骨骼性别确定方法

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Sex determination from skeletal measurements is an important problem in both a forensic and bioarchaeological context. Since the majority of the approaches in the literature employ traditional methods using discriminant functions, a computational machine learning method is proposed based on a fuzzy decision tree implementation presuming it will better overcome the problem's populational dependency, its sensibility to uncertainty and it will also be a valid computational option to the forensic or bioarchaeologic researchers especially for large osteological collections. Constructing fuzzy functions on available statistical information regarding skeletal measurements as basis for the fuzzy decisional process, the proposed method manages to improve by coping with uncertain situations and corroborating the classification factors only at the end of the training process.
机译:在法医和生物考古学背景下,从骨骼测量结果确定性别是一个重要的问题。由于文献中的大多数方法都采用了使用判别函数的传统方法,因此,基于模糊决策树的实现,提出了一种计算机器学习方法,前提是该方法可以更好地克服问题的人口依赖性,对不确定性的敏感性,并且也将是一种可行的方法。法医或生物考古研究人员的有效计算选择,尤其是对于大量骨科疾病的研究。在关于骨骼测量的可用统计信息上构建模糊函数作为模糊决策过程的基础,该方法设法通过在训练过程结束时应对不确定的情况并确认分类因素来进行改进。

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