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Artificial Neural Networks made easy with the FANN library

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28 Aug 2013CPOL24 min read 194.1K   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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>Name</H2
>fann_save_train_internal&nbsp;--&nbsp;Save training data to a file.</DIV
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><code
class="methodsynopsis"
>&#13;  <span
class="type"
>void </span
>fann_save_train_internal(<span
class="methodparam"
><span
class="type"
>struct fann_train_data * </span
><span
class="parameter"
>data</span
></span
><span
class="methodparam"
>, <span
class="type"
>char * </span
><span
class="parameter"
>filename</span
></span
><span
class="methodparam"
>, <span
class="type"
>unsigned int </span
><span
class="parameter"
>save_as_fixed</span
></span
><span
class="methodparam"
>, <span
class="type"
>unsigned int </span
><span
class="parameter"
>decimal_point</span
></span
>);&#13;</code
><P
>&#13;	      Saves the data in <VAR
CLASS="parameter"
>data</VAR
> to <VAR
CLASS="parameter"
>filename</VAR
>.
	      <VAR
CLASS="parameter"
>save_as_fixed</VAR
> is either TRUE or FALSE. <VAR
CLASS="parameter"
>decimal_point</VAR
> tells
	      FANN where the decimal point may be if using fixed point math.
	    </P
><P
>This function appears in FANN &#62;= 1.0.0.</P
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