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77 lines
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HTML
77 lines
3.9 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>返回级联输出变化分数</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-cascade-output-change-fraction" class="refentry">
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<div class="refnamediv">
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<h1 class="refname">fann_get_cascade_output_change_fraction</h1>
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<p class="verinfo">(PECL fann >= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_cascade_output_change_fraction</span> — <span class="dc-title">返回级联输出变化分数</span></p>
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</div>
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<div class="refsect1 description" id="refsect1-function.fann-get-cascade-output-change-fraction-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_cascade_output_change_fraction</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="type">float</span></div>
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<p class="para rdfs-comment">
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级联输出变化分数是一个介于0到1之间的数字，决定了在<span class="function"><a href="fann_get_cascade_output_stagnation_epochs.html" class="function">fann_get_cascade_output_stagnation_epochs()</a></span>的输出连接训练中，<span class="function"><a href="fann_get_mse.html" class="function">fann_get_MSE()</a></span>的值将改变多大才能保持训练不至于停滞。如果训练停滞了， If the training stagnates, 输出连接的训练将结束，新的候选神经元将准备。
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</p>
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<p class="para">
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这就意味着如果在<span class="function"><a href="fann_get_cascade_output_stagnation_epochs.html" class="function">fann_get_cascade_output_stagnation_epochs()</a></span>期间， MSE没有被 <span class="function"><strong>fann_get_cascade_output_change_fraction()</strong></span> 改变, 因为训练的停滞将导致输出连接将被停止。
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</p>
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<p class="para">
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如果级联输出改变分数很小，输出连接将会训练的更多，如果分数很大则会训练的更少。
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</p>
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<p class="para">
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默认的级联输出改变分数是0.01，和MSE中的1%相等。
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</p>
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</div>
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<div class="refsect1 parameters" id="refsect1-function.fann-get-cascade-output-change-fraction-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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</dl>
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</div>
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<div class="refsect1 returnvalues" id="refsect1-function.fann-get-cascade-output-change-fraction-returnvalues">
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<h3 class="title">返回值</h3>
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<p class="para">
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成功，返回级联输出更改分数，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-cascade-output-change-fraction-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_cascade_output_change_fraction.html" class="function" rel="rdfs-seeAlso">fann_set_cascade_output_change_fraction()</a> - 设置级联输出改变分数</span></li>
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<li class="member"><span class="function"><a href="fann_get_mse.html" class="function" rel="rdfs-seeAlso">fann_get_MSE()</a> - 从网络中读取均方误差。</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_output_stagnation_epochs.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_output_stagnation_epochs()</a> - 返回级联输出停滞周期的数量</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> |