模糊聚类分析作为无监督机器学习的主要技术之一，是用模糊理论对重要数据分析和建模的方法，建立了样本类属的不确定性描述，能比较客观地反映现实世界，它已经有效地应用在大规模数据分析、数据挖掘、矢量量化、图像分割、模式识别等领域，具有重要的理论与实际应用价值，随着应用的深入发展，模糊聚类算法的研究不断丰富-Unsupervised fuzzy clustering analysis as the main machine learning techniques is the use of fuzzy theory to important data analysis and modeling method, a sample generic descr iption of the uncertainty, can be more objectively reflect the real world, it has been effectively used in large-scale data analysis, data mining, vector quantization, image segmentation, pattern recognition and other fields, has important theoretical and practical value, with the application of in-depth development, fuzzy clustering algorithm enrich