太阳照射测量的聚类

Anna Szymkowiak-Have, J. Larsen, L. K. Hansen, P. Philipsen, E. Thieden, H. Wulf
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引用次数: 0

摘要

在一项以医学为动机的阳光照射研究中,研究人员从许多受试者中收集了有关太阳习惯的问卷,并对紫外线辐射进行了测量。本文的重点是识别异构数据集中的集群,以了解太阳习惯暴露之间的可能关系,并最终评估皮肤癌的风险。最初为文本和Web挖掘开发的一般概率框架被证明对行为数据的聚类很有用。该框架结合了基于广义高斯混合模型的主成分子空间投影和概率聚类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering of Sun exposure measurements
In a medically motivated Sun-exposure study, questionnaires concerning Sun-habits were collected from a number of subjects together with UV radiation measurements. This paper focuses on identifying clusters in the heterogeneous set of data for the purpose of understanding possible relations between Sun-habits exposure and eventually assessing the risk of skin cancer. A general probabilistic framework originally developed for text and Web mining is demonstrated to be useful for clustering of behavioral data. The framework combines principal component subspace projection with probabilistic clustering based on the generalizable Gaussian mixture model.
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