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Haskell Artificial Neural Networking library
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hann/docs/mini_Network.html

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  1. <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>Network</title><link href="ocean.css" rel="stylesheet" type="text/css" title="Ocean" /><script src="haddock-util.js" type="text/javascript"></script><script type="text/javascript">//<![CDATA[

  2. window.onload = function () {pageLoad();};

  3. //]]>

  4. </script></head><body id="mini"><div id="module-header"><p class="caption">Network</p></div><div id="interface"><h1>Network</h1><div class="top"><p class="src"><span class="keyword">data</span> <a href="Network.html#t:Network" target="main">Network</a> a</p></div><div class="top"><p class="src"><span class="keyword">data</span> <a href="Network.html#t:Layer" target="main">Layer</a> a</p></div><div class="top"><p class="src"><a href="Network.html#v:newNetwork" target="main">newNetwork</a></p></div><div class="top"><p class="src"><a href="Network.html#v:output" target="main">output</a></p></div><h1>Learning functions</h1><div class="top"><p class="src"><a href="Network.html#v:trainShuffled" target="main">trainShuffled</a></p></div><div class="top"><p class="src"><a href="Network.html#v:trainNTimes" target="main">trainNTimes</a></p></div><div class="top"><p class="src"><span class="keyword">data</span> <a href="Network.html#t:CostFunction" target="main">CostFunction</a></p></div><div class="top"><p class="src"><a href="Network.html#v:getDelta" target="main">getDelta</a></p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:LearningRate" target="main">LearningRate</a></p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:Lambda" target="main">Lambda</a></p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:TrainingDataLength" target="main">TrainingDataLength</a></p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:Sample" target="main">Sample</a> a</p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:Samples" target="main">Samples</a> a</p></div><div class="top"><p class="src"><a href="Network.html#v:-45--45--62-" target="main">(--&gt;)</a></p></div><h1>Activation functions</h1><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:ActivationFunction" target="main">ActivationFunction</a> a</p></div><div class="top"><p class="src"><span class="keyword">type</span> <a href="Network.html#t:ActivationFunctionDerivative" target="main">ActivationFunctionDerivative</a> a</p></div><div class="top"><p class="src"><a href="Network.html#v:sigmoid" target="main">sigmoid</a></p></div><div class="top"><p class="src"><a href="Network.html#v:sigmoid-39-" target="main">sigmoid'</a></p></div><h1>Network serialization</h1><div class="top"><p class="src"><a href="Network.html#v:saveNetwork" target="main">saveNetwork</a></p></div><div class="top"><p class="src"><a href="Network.html#v:loadNetwork" target="main">loadNetwork</a></p></div></div></body></html>