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69 lines
2.3 KiB
HTML
69 lines
2.3 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 RPROP 训练的递增系数</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-rprop-increase-factor" class="refentry">
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<div class="refnamediv">
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<h1 class="refname">fann_get_rprop_increase_factor</h1>
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<p class="verinfo">(PECL fann >= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_rprop_increase_factor</span> — <span class="dc-title">返回 RPROP 训练的递增系数</span></p>
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</div>
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<div class="refsect1 description" id="refsect1-function.fann-get-rprop-increase-factor-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_rprop_increase_factor</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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递增系数是一个大于1的值，用于递增 RPROP 训练中的步长。
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</p>
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<p class="para">
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默认的递进系数是 1.2
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</p>
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</div>
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<div class="refsect1 parameters" id="refsect1-function.fann-get-rprop-increase-factor-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-rprop-increase-factor-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，返回递进系数，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-rprop-increase-factor-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_rprop_increase_factor.html" class="function" rel="rdfs-seeAlso">fann_set_rprop_increase_factor()</a> - 使用 RPROP 算法训练时，设置增长因子</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> |