简介:自组织图(Self-Organizing Map,SOM),也称为Kohonen网络,是一种无监督学习算法,用于将高维输入数据映射到低维的拓扑结构中。它主要用于数据的聚类、可视化和特征提取。 自组织图(Self-Organizing Map,SOM),也称为Kohonen网络,是一种无监督学习算法,用于将高维输入数据映射到低维的拓扑结构中。它主要用于数据的...
自组织映射(Self-organization map | SOM) 文章目录 百度百科版本 自组织神经网络SOM是基于无监督学习方法的神经网络的一种重要类型。自组织映射网络理论最早是由芬兰赫尔辛基理工大学Kohen于1981年提出的。此后,伴随着神经网络在20世纪80年代中后期的迅速发展,自组织映射理论及其应用也有了长足的进步。 查看详情 维基百科...
网络释义 1. 自组织映射 贝叶斯自... ... ) self-organizing map 自组织映射 ) self-organization mapping 自组织映射 ) self-organizing maps 自组织映射 ... www.dictall.com|基于2个网页© 2024 Microsoft 隐私声明和 Cookie 法律声明 广告 帮助 反馈...
Self Organization Map for Clustering and Classification in the Ecology of Agent Organizations[J]. Dimuthu Chandana Kelegama,LIU Li hua,LIU Jian qin (College of Information Engineering, Central South University of Technology, Changsha 410083, China).Journal of Central South University of Technology(...
15.Application of self-organization map neural network in intrusion detection自组织映射神经网络在入侵检测中的应用 16.An Self-Organizing Network with Clustering Number Fixed一种确定聚类数目的自组织特征映射网络 17.Application of Self-Organizing Feature Map Neural Network for Data Sorting of Glossal Brim...
The organization in clusters or neurons enables the interpreter to notice patterns and similarities and enables them to analyze seismic facies and better understand the reservoir and other architecture configurations. Consider a previously Z-scored input attribute vector k, chosen from the set of input...
Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of...
Research and development of self-organizing maps algorithm The self-organizing maps(SOM) is an unsupervised learning algorithm,which is capable of self organization and visualization and has been used in many areas... Z Yang,Y Yang - 《Computer Engineering》 被引量: 120发表: 2006年 加载更多来源...
The self-organizing map has the property of effectively creating spatially organized internal representations of various features of input signals and their abstractions. One result of this is that the self-organization process can discover semantic relationships in sentences. Brain maps, semantic maps, ...
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