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📁 Single-layer neural networks can be trained using various learning algorithms. The best-known algori
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"><html><head>  <title></title></head> <body text="#000000" bgcolor="#ffffff" link="#0000ef" vlink="#51188e" alink="#ff0000">  <h3>Adaline, (Optimal) Perceptron and Backpropagation Instructions</h3>  <ul> <li>To specify a training set:</li> </ul>  <ul>   <ol> <li>Select a category to learn, <b>1/red</b> or <b>0/blue</b>.</li>  <li>Click in the plane to place some points.</li>  <li>Then change the category and click to place points in the other category.<br> <br>    </li>   </ol>  <li>To train the network:<br> <br>  </li>    <ol> <li>First select a learning rule by clicking in the pop-up menu (near thetop left of the applet).</li>  <li>Adjust the number of iterations and learning rate parameter in thefields near the bottom of the applet.</li>  <li>Click the <b>Init</b> button to initialize the network to a randomset of weights.</li>  <li>Click the <b>Learn</b> button to train the network.&nbsp; Trainingwill run for the number of iterations (epochs) you specified; you can continue training by clicking again on Learn or clicking the Play button. Clickingthe <b>Play</b> button is like clicking the Learn button repeatedly witha time intervall which you can specify in "delay".</li>  <li>After training, the color of the input plane indicates the output value for that point (0.0=blue, 1.0=red).</li>   </ol>  <li>To compare learning rules, use the same data set each time.&nbsp; When you change the learning rule, don't forget to click the <b>Init </b>button before training.</li>  <li>Click the <b>Clear</b> button to erase the training set.</li> </ul>  <hr width="100%"><a href="index.html">[Back to the Adaline, Perceptron andBackprop applet page</a> ] <br></body></html>

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