A new approach to clustering
A new approach to clustering
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DOI：
10.1016/0031-3203(90)90087-2
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发表时间：
1990-11
期刊：
影响因子：
--
通讯作者：
R. Wilson;M. Spann
中科院分区：
文献类型：
--
作者：
R. Wilson;M. Spann
估计理论是用来推导出一种新的方法来聚类问题。新方法是质心估计和模式估计的统一，考虑了空间尺度对估计量的影响。其结果是一个多分辨率的方法，它跨越了一系列的空间尺度，提高了鲁棒性的数据中的噪声和数据的规模变化，通过使用规模之间的比较作为聚类有效性的测试。迭代和非迭代算法的基础上提出的新的估计，并被证明是更准确的比简单的尺度空间滤波识别和定位的聚类中心，从嘈杂的测试数据。从广泛的应用结果被用来说明新方法的功率和多功能性。
Estimation theory is used to derive a new approach to the clustering problem. The new method is a unification of centroid and mode estimation, achieved by considering the effect of spatial scale on the estimator. The result is a multiresolution method which spans a range of spatial scales, giving enhanced robustness both to noise in the data and to changes of scale in the data, by using comparison between scales as a test of cluster validity. Iterative and non-iterative algorithms based on the new estimator are presented and are shown to be more accurate than simple scale-space filtering in identifying and locating the cluster centres from noisy test data. Results from a wide range of applications are used to illustrate the power and versatility of the new method.