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Artificial Neural Networks made easy with the FANN library

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28 Aug 2013CPOL24 min read 194.2K   10.6K   206  
Neural networks are typically associated with specialised applications, developed only by select groups of experts. This misconception has had a highly negative effect on its popularity. Hopefully, the FANN library will help fill this gap.
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>fann_set_activation_output_steepness</H1
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>Name</H2
>fann_set_activation_output_steepness&nbsp;--&nbsp;Set the steepness of the activation function of the hidden layers.</DIV
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>Description</H2
><code
class="methodsynopsis"
>&#13;  <span
class="type"
>void </span
>fann_set_activation_output_steepness(<span
class="methodparam"
><span
class="type"
>struct fann * </span
><span
class="parameter"
>ann</span
></span
><span
class="methodparam"
>, <span
class="type"
>fann_type </span
><span
class="parameter"
>steepness</span
></span
>);&#13;</code
><P
>&#13;		Set the steepness of the activation function of the hidden layers of 
		<VAR
CLASS="parameter"
>ann</VAR
> to <VAR
CLASS="parameter"
>steepness</VAR
>.
	      </P
><P
>&#13;		The steepness defaults to 0.5 and a larger steepness will make the slope of the
		activation function more steep, while a smaller steepness will make the slope less
		steep. A large steepness is well suited for classification problems while a small
		steepness is well suited for function approximation.
	      </P
><P
>&#13;	        This function is deprecated and will be removed in a future version. Use
	        <A
HREF="r1149.html"
><CODE
CLASS="function"
>fann_set_activation_steepness_output</CODE
></A
> instead.
	      </P
><P
>This function appears in FANN &#62;= 1.0.0. and is deprecated in FANN &#62;= 1.2.0.</P
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