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>fann_print_connections</H1
><DIV
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NAME="AEN449"
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><H2
>Name</H2
>fann_print_connections -- Prints the connections of an ann.</DIV
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><H2
>Description</H2
><code
class="methodsynopsis"
> <span
class="type"
>void </span
>fann_print_connections(<span
class="methodparam"
><span
class="type"
>struct fann * </span
><span
class="parameter"
>ann</span
></span
>); </code
><P
> <CODE
CLASS="function"
>fann_print_connections</CODE
> will print the connections of the ann in a compact matrix, for easy viewing of the internals of the ann.
</P
><P
> The output from fann_print_connections on a small (2 2 1) network trained on the xor problem:
<PRE
CLASS="literallayout"
> Layer / Neuron 012345
L 1 / N 3 ddb...
L 1 / N 4 bbb...
L 2 / N 6 ...cda
</PRE
> This network have five real neurons and two bias neurons. This gives a total of seven neurons named from 0 to 6. The connections between these neurons can be seen in the matrix. <CODE
CLASS="constant"
>"."</CODE
> is a place where there is no connection, while a character tells how strong the connection is on a scale from a-z. The two real neurons in the hidden layer (neuron <CODE
CLASS="constant"
>3</CODE
> and <CODE
CLASS="constant"
>4</CODE
> in layer <CODE
CLASS="constant"
>1</CODE
>) has connection from the three neurons in the previous layer as is visible in the first two lines. The output neuron (<CODE
CLASS="constant"
>6</CODE
>) has connections form the three neurons in the hidden layer <CODE
CLASS="constant"
>3 - 5</CODE
> as is visible in the last line.
</P
><P
> To simplify the matrix output neurons is not visible as neurons that connections can come from, and input and bias neurons are not visible as neurons that connections can go to.
</P
><P
>This function appears in FANN >= 1.2.0.</P
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