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102 lines
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HTML
102 lines
4.1 KiB
HTML
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
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<html>
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<head>
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<meta http-equiv="content-type" content="text/html; charset=UTF-8">
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<title>返回激励函数</title>
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</head>
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<body class="docs"><div id="layout">
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<div id="layout-content"><div id="function.fann-get-activation-function" class="refentry">
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<div class="refnamediv">
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<h1 class="refname">fann_get_activation_function</h1>
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<p class="verinfo">(PECL fann >= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_activation_function</span> — <span class="dc-title">返回激励函数</span></p>
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</div>
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<div class="refsect1 description" id="refsect1-function.fann-get-activation-function-description">
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<h3 class="title">说明</h3>
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<div class="methodsynopsis dc-description">
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<span class="methodname"><strong>fann_get_activation_function</strong></span>
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( <span class="methodparam"><span class="type">resource</span> <code class="parameter">$ann</code></span>
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, <span class="methodparam"><span class="type">int</span> <code class="parameter">$layer</code></span>
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, <span class="methodparam"><span class="type">int</span> <code class="parameter">$neuron</code></span>
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) : <span class="type">int</span></div>
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<p class="para rdfs-comment">
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获取在层数为 <em>layer</em> 的网络中神经元数为 <em>neuron</em>的激励函数，输入层被计为 0.
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</p>
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<p class="para">
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在输入层是不能获取神经元激励函数的。
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</p>
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<p class="para">
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返回值将会是<a href="fann.constants.html#constants.fann-activation-funcs" class="link">激励函数</a> 常量之一。
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</p>
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</div>
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<div class="refsect1 parameters" id="refsect1-function.fann-get-activation-function-parameters">
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<h3 class="title">参数</h3>
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<dl>
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<dt>
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<code class="parameter">ann</code></dt>
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<dd>
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<p class="para">Neural network <span class="type"><a href="language.types.resource.html" class="type resource">resource</a></span>.</p>
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</dd>
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<dt>
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<code class="parameter">layer</code></dt>
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<dd>
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<p class="para">
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层数。
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</p>
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</dd>
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<dt>
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<code class="parameter">neuron</code></dt>
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<dd>
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<p class="para">
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神经元数
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</p>
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</dd>
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</dl>
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</div>
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<div class="refsect1 returnvalues" id="refsect1-function.fann-get-activation-function-returnvalues">
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<h3 class="title">返回值</h3>
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<p class="para">
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<a href="fann.constants.html#constants.fann-train" class="link">学习函数</a> 常量或者如果神经未在神经网络中定义返回 -1， 错误则返回 <strong><code>FALSE</code></strong> .
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</p>
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</div>
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<div class="refsect1 seealso" id="refsect1-function.fann-get-activation-function-seealso">
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<h3 class="title">参见</h3>
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<p class="para">
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<ul class="simplelist">
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<li class="member"><span class="function"><a href="fann_set_activation_function_layer.html" class="function" rel="rdfs-seeAlso">fann_set_activation_function_layer()</a> - 为已应用的层中所有的神经元设置激活函数。</span></li>
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<li class="member"><span class="function"><a href="fann_set_activation_function_hidden.html" class="function" rel="rdfs-seeAlso">fann_set_activation_function_hidden()</a> - 为所有隐藏层设置激活函数</span></li>
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<li class="member"><span class="function"><a href="fann_set_activation_function_output.html" class="function" rel="rdfs-seeAlso">fann_set_activation_function_output()</a> - 为输出层设置激活函数</span></li>
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<li class="member"><span class="function"><a href="fann_set_activation_steepness.html" class="function" rel="rdfs-seeAlso">fann_set_activation_steepness()</a> - 为提供的神经元和层设置激活陡度</span></li>
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<li class="member"><span class="function"><a href="fann_set_activation_function.html" class="function" rel="rdfs-seeAlso">fann_set_activation_function()</a> - 为已应用的神经元和层设置激活函数</span></li>
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</ul>
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</p>
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</div>
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</div></div></div></body></html> |