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<title>BSOM1: Bayesian Self-Organizing Map Ver. 1.0</title><body bgcolor=#ddeeee><h1>BSOM1: Bayesian Self-Organizing Map Ver. 1.0</h1><hr><applet code = "Bsom1.class" width = 420 height = 450><param name = "scale" value = "70" ><param name = "xd" value = "210" ><param name = "input" value = "circ10" ><font color="#ff0000"><h1>Your browser can't interpret java-applets.</h1></font>Please use the newest version of Netscape Navigator or another browser(Internet Explorer, HotJava, etc.) that can interpret (beta) java-applets.The newest version of Netscape Navigator can be gotten from the below site:<br><A HREF="http://home.netscape.com/comprod/mirror/index.html"><IMG SRC="../../gif/netnow3.gif" BORDER=1 WIDTH=88 HEIGHT=31></A></applet><hr><h2>Usage</h2><h3>Input Data</h3>Initially, BSOM reads data from a file specified by the applet parameter `input'.See the source of the present page.A data file must have rows each of which represents the coordinates of a data point.See the contents of <a href="#sample">sample data files</a>.Moreover, data files must be under the directory where this HTML file exists.If you want to change data, enter a new file name in `Input File' and press the return key.If the new data have been read, the centroids and hyperparameters are initialized.<h3>Learn</h3>By pressing the `learn' button, the learning of BSOM is started.In this mode, hyperparameters are controlled manually using the sliders.By pressing the `init' button, the positions of the centroids are initialized randomly.<h3>Auto-Learn</h3>By pressing the 'auto' button, the auto-learning of BSOM is started.In this mode, hyperparameters are tuned by a hyperparameter search algorithm.By pressing the `init' button, the positions of the centroids are initialized randomlyand the hyperparameters are also set to initial values.The auto-learning is suppressed while you grab a slider, <h3>View Density</h3>By pressing the 'density' button, estimated density for the data is calculatedand displayed using the gray scale.In addition, the present values of hyperparameters are displayed.In this mode, the other processes are suspended. The suspended processes are restarted by making this mode off.The resolution of density calculation isspecified by `dstep', which is the pixel size of a cell.Small dstep requires large calculation times.<h3>Change Unit Size</h3>If you want to change the number of units, enter the number to `#unit' and press the return key.This value must be larger than 1 and smaller than 100.Initial setting after changing the unit size takes somewhat of time.<h3>Output Results</h3>By pressing the `output' button, the present coordinates of the centroids are outputted.In case of Netscape Navigator, the results are outputted to the java console,if it is made usable in the `Options' menu.In case of Internet Explorer 3, the results are outputted to the java log file,if is is made usable in the option setting.Appletviewer in JDK is most usable since the results are outputted to the standard output.<h3>Applet Parameters</h3>See the header of the source file <a href="Bsom1.java">Bsom1.java</a><p><hr><a name="sample"><h2>Sample Data Files</h2></a>Each sample data set is made by adding Gaussian noise to points ona simple mathematical curve.The number of data points (n) or the standard deviation of the noise (sd)is changed.<ul> <li> Sine+Gaussian Noise(sd=1/10) <ul> <li> <a href="sin20">sin20</a> : n=20 <li> <a href="sin50">sin50</a> : n=50 <li> <a href="sin500">sin500</a> : n=500 </ul> <li> Circle+Gaussian Noise(n=100) <ul> <li> <a href="circ10">circ10</a> : sd=1/10 <li> <a href="circ5">circ5</a> : sd=1/5 <li> <a href="circ3">circ3</a> : sd=1/3 <li> <a href="circ2">circ2</a> : sd=1/2 </ul></ul><hr><h2>Note</h2>(1)Netscape Navigator 3 on Windows has a bug that applet parameters are ignoredunless its document encoding is Latin-1.Thus, you need to set the encoding to Latin-1.<p>(2)I strongly recommend using browsers with a just-in-time (JIT) compiler.Calculation on the other browsers is rather slow.<p>(3)When the hyperparameters are not changed in the auto-learning at the start, you should increase beta slowly using the slider for a while.<p>(4)The newest information is in my <a href="http://www.aist.go.jp/NIBH/~b0616/Lab/index-e.html">`Neural Network Lab Page'</a>.<p><hr><p>Akio Utsugi <address><a href="mailto:utsugi@nibh.go.jp">utsugi@nibh.go.jp</a></address><p>Nov 20 1996 created</body>⌨️ 快捷键说明
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