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?>
<div id="function.fann-get-activation-steepness" class="refentry">
 <div class="refnamediv">
  <h1 class="refname">fann_get_activation_steepness</h1>
  <p class="verinfo">(PECL fann &gt;= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_activation_steepness</span> &mdash; <span class="dc-title">为提供的神经和网络层数返回激活陡度</span></p>

 </div>

 <div class="refsect1 description" id="refsect1-function.fann-get-activation-steepness-description">
  <h3 class="title">说明</h3>
  <div class="methodsynopsis dc-description">
   <span class="methodname"><strong>fann_get_activation_steepness</strong></span>(<span class="methodparam"><span class="type"><a href="language.types.resource.php" class="type resource">resource</a></span> <code class="parameter">$ann</code></span>, <span class="methodparam"><span class="type"><a href="language.types.integer.php" class="type int">int</a></span> <code class="parameter">$layer</code></span>, <span class="methodparam"><span class="type"><a href="language.types.integer.php" class="type int">int</a></span> <code class="parameter">$neuron</code></span>): <span class="type"><a href="language.types.float.php" class="type float">float</a></span></div>

  <p class="para rdfs-comment">
   获取神经元数为 <code class="literal">neuron</code> 层数为
   <code class="literal">layer</code>神经网络的激活陡度，将输入层数计为1层。
  </p>
  <p class="para">
   在输入层中是不可能获取激活陡度。
  </p>
  <p class="para">
   激活函数的陡度表明了激活函数从最小到最大有多块。一个高值表明将会提供一个更高效的训练。
  </p>
  <p class="para">
   在训练神经网络时，输出值应该处于极端(通常是 0 和 1，取决于激励函数)，一般陡峭的激活函数将会被使用(比如为1.0时)。
  </p>
  <p class="para">
   默认的激活陡度是0.5.
  </p>
 </div>


 <div class="refsect1 parameters" id="refsect1-function.fann-get-activation-steepness-parameters">
  <h3 class="title">参数</h3>
  <dl>
   
    <dt><code class="parameter">ann</code></dt>
    <dd>
     <p class="para">神经网络 <span class="type">资源</span>。</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-get-activation-steepness-returnvalues">
  <h3 class="title">返回值</h3>
  <p class="para">
   激活陡度，当神经元在神经网络中没定义时为-1，错误时返回 <strong><code><a href="reserved.constants.php#constant.false">false</a></code></strong> .
  </p>
 </div>


 <div class="refsect1 seealso" id="refsect1-function.fann-get-activation-steepness-seealso">
  <h3 class="title">参见</h3>
  <p class="para">
   <ul class="simplelist">
    <li><span class="function"><a href="function.fann-set-activation-function.php" 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>
    <li><span class="function"><a href="function.fann-set-activation-steepness-layer.php" 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><span class="function"><a href="function.fann-set-activation-steepness-hidden.php" 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><span class="function"><a href="function.fann-set-activation-steepness-output.php" 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><span class="function"><a href="function.fann-set-activation-steepness.php" 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>
   </ul>
  </p>
 </div>



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