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<title>Feedforward neural networks 3. FFNet versus discriminant classifier</title></head><body bgcolor="#FFFFFF">

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Feedforward neural networks 3. FFNet versus discriminant classifier
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You might want to compare the FFNet classifier with a discriminant classifier. Unlike the FFNet, a <a href="Discriminant.html">discriminant</a> classifier does not need any iterative procedure in the learning phase and can be used immediately after creation for classification. The following three simple steps will give you the confusion matrix based on discriminant analysis:</p>
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1. Select the Pattern and the Categories together and choose <b>To Discriminant</b>.  A newly created Discriminant will appear.
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2. Select the Discriminant and the Pattern together and choose <b>To Categories...</b>. A newly created <a href="Categories.html">Categories</a> will appear.
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3. Select the two appropriate Categories and choose <a href="Categories__To_Confusion.html">To Confusion</a>.  A newly created <a href="Confusion.html">Confusion</a> will appear. After pushing the <a href="Info.html">Info</a> button, the info window will show you the fraction correct.
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See also the <a href="Discriminant_analysis.html">Discriminant analysis</a> tutorial for more information.</p>
<h3>Links to this page</h3>
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<li><a href="Feedforward_neural_networks.html">Feedforward neural networks</a>
<li><a href="Feedforward_neural_networks_2__Quick_start.html">Feedforward neural networks 2. Quick start</a>
</ul>
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	<p>&copy; djmw, April 26, 2004</p>
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