Self-organizing map (SOM) used provides a unique and integrating neural network approach for proper and effective initial analysis of multidimensional financial and economic data. We provide a brief sketch of the...
Self Organizing Maps (SOM): 一种基于神经网络的聚类算法 自组织映射神经网络, 即Self Organizing Maps (SOM), 可以对数据进行无监督学习聚类。它的思想很简单,本质上是一种只有输入层--隐藏层的神经网络。隐藏层中的一个节点代表一个需要聚成的类。训练时采用“竞争学习”的方式,每个输入的样例在隐藏层中找到一...
Randomize the map's nodes' weight vectors:对竞争层(也是输出层)各神经元权重赋小随机数初值,并进行归一化处理,归一化处理有助于提高运算性能 Grab an input vector :获取输入向量,并对数据进行归一化处理 Traverse each node in the map:不断提供新样本、进行训练 Use theEuclidean distanceformula to find the...
system.time(som_model<-supersom(sample,grid=som_grid,keep.data=TRUE))#计算一下运行时间plot(som_model,type="changes")plot(som_model,type="codes",codeRendering="segments")som_cluster<-cutree(hclust(dist(as.matrix(as.data.frame(som_model$codes))),6)#使用层次聚类进行分类add.cluster.boundaries...
SelfSelf--organizingorganizing--mapmap--based molecular based molecular:自我———基于基于organizingorganizing mapmap分子分子Ba,帮助,Based,based,self 文档格式: .pdf 文档大小: 462.95K 文档页数: 48页 顶/踩数: 0/0 收藏人数: 0 评论次数: 0 文档...
Self-organizing map for cluster analysis of aof,a,A,map,for,Self,ofa,maps,Map,For 文档格式: .pdf 文档大小: 217.86K 文档页数: 15页 顶/踩数: 0/0 收藏人数: 0 评论次数: 0 文档热度: 文档分类: 论文--毕业论文 文档标签: ofaAmapforSelfofamapsMapFor ...
self-organizing map(SOM) 是一种被无监督学习训练产生的一个低维(通常为二维)的人工神经网络,可作为一种进行降维的方法。在高通量测序数据中可作为一种将不同样本的特征聚类的可视化方式。 R 实现:oposSOM包 oposSOM软件包仅需要输入以基因表达矩阵数据,例如经过标准化处理microarray 数据或RNA-seq数据。
After the array of map units have been initialized to some value, each input data field is compared to the array of map units. As in EOF analysis, both the input data and the map units are converted to vector form and the Euclidean distance measured between the input data and each map ...
A self-organizing map (SOM) was used to identify clusters in a large (2258 cases), heterogeneous computer-aided diagnosis database based on mammographic findings (BI-RADS) and patient age. The resulting clusters were then characterized by their prototypes determined using a constraint satisfaction ...
et al. Surface current patterns in the northern Adriatic extracted from High-Frequency radar data using Self- Organizing Map analysis, J. Geophys. Res. 116, C08033 (2011). 23. Shchepetkin, A. F. & McWilliams, J. C. The regional oceanic modeling system (ROMS): A split-explicit, free...