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<!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>返回训练期间使用的候选数量</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-num-candidates" class="refentry">
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<div class="refnamediv">
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<h1 class="refname">fann_get_cascade_num_candidates</h1>
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<p class="verinfo">(PECL fann >= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_cascade_num_candidates</span> — <span class="dc-title">返回训练期间使用的候选数量</span></p>
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</div>
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<div class="refsect1 description" id="refsect1-function.fann-get-cascade-num-candidates-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_num_candidates</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">int</span></div>
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<p class="para rdfs-comment">
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返回训练期间使用的候选数量 (
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<span class="function"><a href="fann_get_cascade_activation_functions_count.html" class="function">fann_get_cascade_activation_functions_count()</a></span>,
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<span class="function"><a href="fann_get_cascade_activation_steepnesses_count.html" class="function">fann_get_cascade_activation_steepnesses_count()</a></span> 和
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<span class="function"><a href="fann_get_cascade_num_candidate_groups.html" class="function">fann_get_cascade_num_candidate_groups()</a></span>)的和。
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</p>
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<p class="para">
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实际的候选数是由 <span class="function"><a href="fann_get_cascade_activation_functions.html" class="function">fann_get_cascade_activation_functions()</a></span> 和
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<span class="function"><a href="fann_get_cascade_activation_steepnesses.html" class="function">fann_get_cascade_activation_steepnesses()</a></span> 数组定义的。 这些数组定义的激活功能和激活的陡度用于候选神经元。如果在激活函数数组中有两个激活函数并且陡度数组中有三个陡度，则将会有2x3=6个不同的候选神经元被训练。 这6个不同的候选神经元将会被复制到几个候选组中，这些候选组不同之处在于他们的初始权重。如果组的数量设为2，则候选神经元的数量为2x3x2=12.候选组的数量是有 <span class="function"><a href="fann_set_cascade_num_candidate_groups.html" class="function">fann_set_cascade_num_candidate_groups()</a></span> 函数定义的。
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</p>
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<p class="para">
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默认的候选神经元数量为 6x4x2 = 48
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</p>
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</div>
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<div class="refsect1 parameters" id="refsect1-function.fann-get-cascade-num-candidates-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-num-candidates-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，返回训练期间候选神经元的数量，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-num-candidates-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_get_cascade_activation_functions.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_functions()</a> - 返回级联激活函数</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_functions_count.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_functions_count()</a> - 返回级联激活函数的数量</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_steepnesses.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_steepnesses()</a> - 返回级联激活陡度</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_steepnesses_count.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_steepnesses_count()</a> - 激活陡度的数量</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_num_candidate_groups.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_num_candidate_groups()</a> - 返回候选组的数量</span></li>
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</ul>
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</p>
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</div>
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<!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>返回训练期间使用的候选数量</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-num-candidates" class="refentry">
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<div class="refnamediv">
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<h1 class="refname">fann_get_cascade_num_candidates</h1>
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<p class="verinfo">(PECL fann >= 1.0.0)</p><p class="refpurpose"><span class="refname">fann_get_cascade_num_candidates</span> — <span class="dc-title">返回训练期间使用的候选数量</span></p>
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</div>
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<div class="refsect1 description" id="refsect1-function.fann-get-cascade-num-candidates-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_num_candidates</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">int</span></div>
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<p class="para rdfs-comment">
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返回训练期间使用的候选数量 (
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<span class="function"><a href="fann_get_cascade_activation_functions_count.html" class="function">fann_get_cascade_activation_functions_count()</a></span>,
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<span class="function"><a href="fann_get_cascade_activation_steepnesses_count.html" class="function">fann_get_cascade_activation_steepnesses_count()</a></span> 和
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<span class="function"><a href="fann_get_cascade_num_candidate_groups.html" class="function">fann_get_cascade_num_candidate_groups()</a></span>)的和。
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</p>
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<p class="para">
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实际的候选数是由 <span class="function"><a href="fann_get_cascade_activation_functions.html" class="function">fann_get_cascade_activation_functions()</a></span> 和
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<span class="function"><a href="fann_get_cascade_activation_steepnesses.html" class="function">fann_get_cascade_activation_steepnesses()</a></span> 数组定义的。 这些数组定义的激活功能和激活的陡度用于候选神经元。如果在激活函数数组中有两个激活函数并且陡度数组中有三个陡度，则将会有2x3=6个不同的候选神经元被训练。 这6个不同的候选神经元将会被复制到几个候选组中，这些候选组不同之处在于他们的初始权重。如果组的数量设为2，则候选神经元的数量为2x3x2=12.候选组的数量是有 <span class="function"><a href="fann_set_cascade_num_candidate_groups.html" class="function">fann_set_cascade_num_candidate_groups()</a></span> 函数定义的。
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</p>
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<p class="para">
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默认的候选神经元数量为 6x4x2 = 48
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</p>
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</div>
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<div class="refsect1 parameters" id="refsect1-function.fann-get-cascade-num-candidates-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-num-candidates-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，返回训练期间候选神经元的数量，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-num-candidates-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_get_cascade_activation_functions.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_functions()</a> - 返回级联激活函数</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_functions_count.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_functions_count()</a> - 返回级联激活函数的数量</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_steepnesses.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_steepnesses()</a> - 返回级联激活陡度</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_activation_steepnesses_count.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_activation_steepnesses_count()</a> - 激活陡度的数量</span></li>
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<li class="member"><span class="function"><a href="fann_get_cascade_num_candidate_groups.html" class="function" rel="rdfs-seeAlso">fann_get_cascade_num_candidate_groups()</a> - 返回候选组的数量</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>
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