⭐ 欢迎来到虫虫下载站! | 📦 资源下载 📁 资源专辑 ℹ️ 关于我们
⭐ 虫虫下载站

📄 som_fuzzycolor.html

📁 Kohonen的SOM软件包
💻 HTML
字号:
<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML//EN"><html><head><title>SOM Toolbox / som_fuzzycolor </title></head><body bgcolor=#f0f0f0><table border=0 width="100%" cellpadding=0 cellspacing=0><tr><td valign=baseline><font size=+2>SOM Toolbox</font></td><td valign=baseline align=center><a href="somtoolbox.html">Online documentation</td><td valign=baseline align=right><a href="http://www.cis.hut.fi/projects/somtoolbox/" target="_top">http://www.cis.hut.fi/projects/somtoolbox/</a></td></tr></table><hr><H1> som_fuzzycolor </H1><P><B> [color,X]=som_fuzzycolor(sM,T,R,mode,initRGB,S)</B></P><PRE> SOM_FUZZYCOLOR Heuristic contraction projection/soft cluster color coding for SOM   function [color,X]=som_softcolor(map,T,R,mode,initRGB,S)  sM        (map struct)  [T]       (scalar) parameter that defines the speed of contraction               T<1: slow contraction, T>1: fast contraction. Default: 1  [R]       (scalar) number of rounds, default: 30  [mode]    (string) 'lin' or 'exp', default: 'lin'    [initRGB] (string) Strings accepted by SOM_COLORCODE,  default: 'rgb2'  [S]       (matrix) MxM matrix a precalculated similarity matrix   color     (matrix) of size MxRx3 resulting color codes at each step   X         (matrix) of size MxRx2 coordiantes for projected unit weight vectors              at each step of iteration. (Color code C is calculated using this             projection.) The idea of the projection is to use a naive contraction model which pulls the units  together. Units that are close to each other in the output space (clusters)  contract faster into the same point in the projection. The original position for  each unit is its location in the topological grid.   This is an explorative tool to color code the map units so that similar units  (in the sense of euclidean norm) have similar coloring (See also SOM_KMEANSCOLOR)  The tool gives a series of color codings which start from an initial color coding  (see SOM_COLORCODE) and show the how the fuzzy clustering process evolves.  The speed of contraction is controlled by the input parameter T. If it is high the projection contracts more slowly and reveals more intermediate stages (hierarchy). A good value for T must be searched manually. It is probable that the  default values do not yield good results. If the conatrction process may be slow. In this case the mode can be set to 'exp' instead of 'lin', however, then the computing becomes heavier. EXAMPLE  load iris; % or any other map struct sM   [color]=som_fuzzycolor(sM,'lin',10);  som_show(sM,'color',color); See also SOM_KMEANSCOLOR, SOM_COLORCODE, SOM_CLUSTERCOLOR REFERENCES  Johan Himberg, "A SOM Based Cluster Visualization and Its Application for False Coloring", in Proceedings of International Joint Conference on Neural Networks (IJCNN2000)},  pp. 587--592,Vol. 3, 2000  Esa Alhoniemi, Johan Himberg, and Juha Vesanto, Probabilistic Measures for Responses of Self-Organizing Map Units, pp. 286--290, in Proceedings of the International ICSC Congress  on Computational Intelligence Methods and Applications (CIMA '99)}, ICSC Academic Press}, 1999 Outline of the heuristic First a matrix D of squared pairwise euclidean distances D(i,j)=d(i,j)^2 between  map weight vectors is calculated. This matrix is transformed into a similarity matrix S,  s(i,j)=exp(-(D(i,j)/(T.^2*v)), where T is a free input parameter and v the variance of  all elements of D v=var(D(:)). The matrix is further normalized so that all rows sum to  one. The original topological coordinates X=som_unit_coords(sM) are successively  averaged using this matrix. X(:,:,i)=S^i*X(:,:,1); As the process is actually a series  of successive weighted averagings of the initial coordinates, all projected points  eventually contract into one point.  T is a user defined parameter that defines how fast  the projection contracts into  this center point. If T is too small, the process will  end into the center point at once.  In practise, we don't calculate powers of S, but compute   X(:,:,i)=S.*X(:,:,i-1); % mode: 'lin' The contraction process may be slow if T is selected to be large,  then for each step the similarity matrix is squared   X(:,:,i)=S*X(:,:,1); S=S*S % mode: 'exp' The coloring is done using the function SOM_COLORCODE according to the  projections in X, The coordinates are rescaled in order to achieve maximum  color resolution.</PRE><p><hr><br><center>[ <a href="somtoolbox.html">SOM Toolbox online doc</a> ]</center><br><!-- Last updated: May 30 2002 --></body></html>

⌨️ 快捷键说明

复制代码 Ctrl + C
搜索代码 Ctrl + F
全屏模式 F11
切换主题 Ctrl + Shift + D
显示快捷键 ?
增大字号 Ctrl + =
减小字号 Ctrl + -