Clustering is one of the most fundamental and essential data analysis tasks with broad applications. It has been studied in various research fields: data mining, machine learning, pattern recognition and in engineering, economics and biomedical data analysis. Headache is not a disease that typically shortens one’s life, but it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European community. This paper is focused on a new strategy based on a hybrid model for combining fuzzy partition method and maximum likelihood estimation clustering algorithm for diagnosing primary headache disorder. The proposed hybrid system is tested on two data sets for diagnosing headache disorder collected from Clinical Centre of Vojvodina in Serbia.

中文翻译：

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诊断原发性头痛疾病的混合模糊聚类方法

群集是具有广泛应用程序的最基本和必不可少的数据分析任务之一。已经在各种研究领域中进行了研究：数据挖掘，机器学习，模式识别以及工程，经济学和生物医学数据分析。头痛不是通常会缩短人寿的疾病，但它可能是严重的社会问题，也可能是健康问题。由于欧洲共同体工作效率的降低，每年大约损失270亿欧元。本文重点研究了一种基于混合模型的新策略，该策略结合了模糊分区方法和最大似然估计聚类算法来诊断原发性头痛疾病。在从塞尔维亚伏伊伏丁那临床中心收集的两个用于诊断头痛疾病的数据集上对提出的混合系统进行了测试。