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<refentry xml:id="function.fann-get-activation-steepness" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
 <refnamediv>
  <refname>fann_get_activation_steepness</refname>
  <refpurpose>Returns the activation steepness for supplied neuron and layer number</refpurpose>
 </refnamediv>

 <refsect1 role="description">
  &reftitle.description;
  <methodsynopsis>
   <type>float</type><methodname>fann_get_activation_steepness</methodname>
   <methodparam><type>resource</type><parameter>ann</parameter></methodparam>
   <methodparam><type>int</type><parameter>layer</parameter></methodparam>
   <methodparam><type>int</type><parameter>neuron</parameter></methodparam>
  </methodsynopsis>
  <para>
   Get the activation steepness for neuron number <literal>neuron</literal> in layer number
   <literal>layer</literal>, counting the input layer as layer 0.
  </para>
  <para>
   It is not possible to get activation steepness for the neurons in the input layer.
  </para>
  <para>
   The steepness of an activation function says something about how fast the activation function goes
   from the minimum to the maximum.  A high value for the activation function will also give a more aggressive training.
  </para>
  <para>
   When training neural networks where the output values should be at the extremes
   (usually 0 and 1, depending on the activation function), a steep activation function can be used (e.g.  1.0).
  </para>
  <para>
   The default activation steepness is 0.5.
  </para>
 </refsect1>

 <refsect1 role="parameters">
  &reftitle.parameters;
  <variablelist>
   <varlistentry>
    <term><parameter>ann</parameter></term>
    <listitem>
     &fann.ann.description;
    </listitem>
   </varlistentry>
   <varlistentry>
    <term><parameter>layer</parameter></term>
    <listitem>
     <para>
      Layer number
     </para>
    </listitem>
   </varlistentry>
   <varlistentry>
    <term><parameter>neuron</parameter></term>
    <listitem>
     <para>
      Neuron number
     </para>
    </listitem>
   </varlistentry>
  </variablelist>
 </refsect1>

 <refsect1 role="returnvalues">
  &reftitle.returnvalues;
  <para>
   The activation steepness for the neuron or -1 if the neuron is not defined in the neural network, or &false; on error.
  </para>
 </refsect1>

 <refsect1 role="seealso">
  &reftitle.seealso;
  <para>
   <simplelist>
    <member><function>fann_set_activation_function</function></member>
    <member><function>fann_set_activation_steepness_layer</function></member>
    <member><function>fann_set_activation_steepness_hidden</function></member>
    <member><function>fann_set_activation_steepness_output</function></member>
    <member><function>fann_set_activation_steepness</function></member>
   </simplelist>
  </para>
 </refsect1>


</refentry>

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