Effective data discretization can obviously improve system ability on clustering instances, and can also make systems more robust to data noise.
有效的离散化可以显著地提高系统对样本的聚类能力，增强系统对数据噪音的鲁棒性。
Attribute means clustering is more robust than fuzzy means clustering by theoretical analysis and numerical example.
通过理论分析，属性均值聚类是比模糊均值聚类更稳健的聚类方法。
Gaussian Mixture Density Modelling and Decomposition (GMDD) is a hierarchical clustering method based on robust statistical theory.
高斯混合密度降解模型(GMDD)是一种基于稳健统计理论的层次聚类方法。
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