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?>
<div id="function.fann-cascadetrain-on-data" class="refentry">
 <div class="refnamediv">
  <h1 class="refname">fann_cascadetrain_on_data</h1>
  <p class="verinfo">(PECL fann &gt;= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_cascadetrain_on_data</span> &mdash; <span class="dc-title">在整个数据集上训练，使用一段时间的 Cascade2 训练算法。</span></p>

 </div>

 <div class="refsect1 description" id="refsect1-function.fann-cascadetrain-on-data-description">
  <h3 class="title">说明</h3>
  <div class="methodsynopsis dc-description">
   <span class="methodname"><strong>fann_cascadetrain_on_data</strong></span>(<br>&nbsp;&nbsp;&nbsp;&nbsp;<span class="methodparam"><span class="type"><a href="language.types.resource.php" class="type resource">resource</a></span> <code class="parameter">$ann</code></span>,<br>&nbsp;&nbsp;&nbsp;&nbsp;<span class="methodparam"><span class="type"><a href="language.types.resource.php" class="type resource">resource</a></span> <code class="parameter">$data</code></span>,<br>&nbsp;&nbsp;&nbsp;&nbsp;<span class="methodparam"><span class="type"><a href="language.types.integer.php" class="type int">int</a></span> <code class="parameter">$max_neurons</code></span>,<br>&nbsp;&nbsp;&nbsp;&nbsp;<span class="methodparam"><span class="type"><a href="language.types.integer.php" class="type int">int</a></span> <code class="parameter">$neurons_between_reports</code></span>,<br>&nbsp;&nbsp;&nbsp;&nbsp;<span class="methodparam"><span class="type"><a href="language.types.float.php" class="type float">float</a></span> <code class="parameter">$desired_error</code></span><br>): <span class="type"><a href="language.types.boolean.php" class="type bool">bool</a></span></div>

  <p class="para rdfs-comment">
   级联输出改变小数是一个0到1之间的数字，表示在输出连接的训练中，为了使训练不停滞的情况下，经过 <span class="function"><a href="function.fann-get-cascade-output-stagnation-epochs.php" class="function">fann_get_cascade_output_stagnation_epochs()</a></span> 次迭代的后，<span class="function"><a href="function.fann-get-mse.php" class="function">fann_get_MSE()</a></span> 将会改变多大。如果训练停滞了，训练的输出连接将会结束，新的候选神经元将会准备好。
  </p>
  <p class="para">
   该训练使用由 fann_set_cascade_ 前缀设置的参数，但它也采用了另一种训练算法，即内部训练算法。该训练算法要么是 <span class="function"><a href="function.fann-set-training-algorithm.php" class="function">fann_set_training_algorithm()</a></span> 设置的 <strong><code><a href="fann.constants.php#constant.fann-train-rprop">FANN_TRAIN_RPROP</a></code></strong> 算法，要么是 <strong><code><a href="fann.constants.php#constant.fann-train-quickprop">FANN_TRAIN_QUICKPROP</a></code></strong>，这些算法设置的参数同样也会影响到级联训练。
  </p>
 </div>


 <div class="refsect1 parameters" id="refsect1-function.fann-cascadetrain-on-data-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">data</code></dt>
    <dd>
     <p class="para">神经网络训练数据 <span class="type">资源</span>。</p>
    </dd>
   
   
    <dt><code class="parameter">max_neurons</code></dt>
    <dd>
     <p class="para">
     被添加入神经网络中最大的神经元数。
     </p>
    </dd>
   
   
    <dt><code class="parameter">neurons_between_reports</code></dt>
    <dd>
     <p class="para">
      打印状态报告之间的神经元数。0表示没有报告会被打印。
     </p>
    </dd>
   
   
    <dt><code class="parameter">desired_error</code></dt>
    <dd>
     <p class="para">
      预期的 <span class="function"><a href="function.fann-get-mse.php" class="function">fann_get_MSE()</a></span> 或 <span class="function"><a href="function.fann-get-bit-fail.php" class="function">fann_get_bit_fail()</a></span>,
      取决于 <span class="function"><a href="function.fann-set-train-stop-function.php" class="function">fann_set_train_stop_function()</a></span> 选择的停止函数
     </p>
    </dd>
   
  </dl>
 </div>


 <div class="refsect1 returnvalues" id="refsect1-function.fann-cascadetrain-on-data-returnvalues">
  <h3 class="title">返回值</h3>
  <p class="para">成功时返回 <strong><code><a href="reserved.constants.php#constant.true">true</a></code></strong>，其它情况下返回 <strong><code><a href="reserved.constants.php#constant.false">false</a></code></strong>。</p>
 </div>


 <div class="refsect1 seealso" id="refsect1-function.fann-cascadetrain-on-data-seealso">
  <h3 class="title">参见</h3>
  <p class="para">
   <ul class="simplelist">
    <li><span class="function"><a href="function.fann-train-on-data.php" class="function" rel="rdfs-seeAlso">fann_train_on_data()</a> - 在整个数据集上训练一段时间。</span></li>
    <li><span class="function"><a href="function.fann-cascadetrain-on-file.php" class="function" rel="rdfs-seeAlso">fann_cascadetrain_on_file()</a> - 读取文件并在整个数据集上训练，使用 Cascade2 训练算法训练一段时间</span></li>
   </ul>
  </p>
 </div>



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