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<title>为提供的神经元和层设置激活陡度</title>
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<body class="docs"><div id="layout">
<div id="layout-content"><div id="function.fann-set-activation-steepness" class="refentry">
<div class="refnamediv">
<h1 class="refname">fann_set_activation_steepness</h1>
<p class="verinfo">(PECL fann &gt;= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_set_activation_steepness</span> &mdash; <span class="dc-title">为提供的神经元和层设置激活陡度</span></p>
</div>
<div class="refsect1 description" id="refsect1-function.fann-set-activation-steepness-description">
<h3 class="title">说明</h3>
<div class="methodsynopsis dc-description">
<span class="methodname"><strong>fann_set_activation_steepness</strong></span>
( <span class="methodparam"><span class="type">resource</span> <code class="parameter">$ann</code></span>
, <span class="methodparam"><span class="type">float</span> <code class="parameter">$activation_steepness</code></span>
, <span class="methodparam"><span class="type">int</span> <code class="parameter">$layer</code></span>
, <span class="methodparam"><span class="type">int</span> <code class="parameter">$neuron</code></span>
) : <span class="type">bool</span></div>
<p class="para rdfs-comment">
为层数为 <em>layer</em>,神经元数为 <em>neuron</em> 的神经元设置激活陡度输出层的层数计为0。
</p>
<p class="para">
为输入层中的神经元设置激活陡度是不可能的。.
</p>
<p class="para">
激活函数的陡度表示激活从最大值到最小值有多快。一个高的激活函数值也会导致一个更积极的训练。
</p>
<p class="para">
当训练神经网络中输出值处于一个极端值(通常为0或者1取决于激活函数)时,可以使用陡峭的激活函数(比如 1.0)。
</p>
<p class="para">
默认激活陡度是0.5。
</p>
</div>
<div class="refsect1 parameters" id="refsect1-function.fann-set-activation-steepness-parameters">
<h3 class="title">参数</h3>
<dl>
<dt>
<code class="parameter">ann</code></dt>
<dd>
<p class="para">Neural network <span class="type"><a href="language.types.resource.html" class="type resource">resource</a></span>.</p>
</dd>
<dt>
<code class="parameter">activation_steepness</code></dt>
<dd>
<p class="para">
激活陡度。
</p>
</dd>
<dt>
<code class="parameter">layer</code></dt>
<dd>
<p class="para">
层数。
</p>
</dd>
<dt>
<code class="parameter">neuron</code></dt>
<dd>
<p class="para">
神经元数。
</p>
</dd>
</dl>
</div>
<div class="refsect1 returnvalues" id="refsect1-function.fann-set-activation-steepness-returnvalues">
<h3 class="title">返回值</h3>
<p class="para">Returns <strong><code>TRUE</code></strong> on success, or <strong><code>FALSE</code></strong> otherwise.</p>
</div>
<div class="refsect1 seealso" id="refsect1-function.fann-set-activation-steepness-seealso">
<h3 class="title">参见</h3>
<p class="para">
<ul class="simplelist">
<li class="member"><span class="function"><a href="fann_set_activation_steepness_layer.html" class="function" rel="rdfs-seeAlso">fann_set_activation_steepness_layer()</a> - 为提供的层中所有的神经元设置激活陡度</span></li>
<li class="member"><span class="function"><a href="fann_set_activation_steepness_hidden.html" class="function" rel="rdfs-seeAlso">fann_set_activation_steepness_hidden()</a> - 为所有隐藏层中所有的神经元设置激活函数陡度</span></li>
<li class="member"><span class="function"><a href="fann_set_activation_steepness_output.html" class="function" rel="rdfs-seeAlso">fann_set_activation_steepness_output()</a> - 在输出层中设置激活陡度</span></li>
<li class="member"><span class="function"><a href="fann_get_activation_steepness.html" class="function" rel="rdfs-seeAlso">fann_get_activation_steepness()</a> - 为提供的神经和网络层数返回激活陡度</span></li>
<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>
</ul>
</p>
</div>
</div></div></div></body></html>