一种基于属性值变化程度定权的聚类算法A weighted clustering algorithm based on attribute's variation
杨扬,许厚泽,常军
摘要(Abstract)：
针对经典K-means聚类算法以欧氏距离作为相似度判断法则进行聚类划分,而未考虑聚类对象的各属性值对聚类划分的影响程度存在差异的问题,该文提出了一种基于属性值变化程度定权的聚类算法。通过采用Iris dataset数据进行实验,该算法相对于其他聚类算法获得了更好的聚类效果,且该算法适用于生物物种分类、遥感影像识别等工作领域,能提高聚类运算的精准度。
关键词(KeyWords)： 聚类算法;K-means;定权;属性值
基金项目(Foundation): 国家自然科学基金项目(41374021)
作者(Author): 杨扬,许厚泽,常军
DOI: 10.16251/j.cnki.1009-2307.2018.05.001
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