|
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<HTML
><HEAD
><TITLE
>Network Design</TITLE
><link href="../style.css" rel="stylesheet" type="text/css"><META
NAME="GENERATOR"
CONTENT="Modular DocBook HTML Stylesheet Version 1.7"><LINK
REL="HOME"
TITLE="Fast Artificial Neural Network Library"
HREF="index.html"><LINK
REL="UP"
TITLE="Advanced Usage"
HREF="c104.html"><LINK
REL="PREVIOUS"
TITLE="Advanced Usage"
HREF="c104.html"><LINK
REL="NEXT"
TITLE="Understanding the Error Value"
HREF="x148.html"></HEAD
><BODY
CLASS="section"
BGCOLOR="#FFFFFF"
TEXT="#000000"
LINK="#0000FF"
VLINK="#840084"
ALINK="#0000FF"
><DIV
CLASS="NAVHEADER"
><TABLE
SUMMARY="Header navigation table"
WIDTH="100%"
BORDER="0"
CELLPADDING="0"
CELLSPACING="0"
><TR
><TH
COLSPAN="3"
ALIGN="center"
>Fast Artificial Neural Network Library</TH
></TR
><TR
><TD
WIDTH="10%"
ALIGN="left"
VALIGN="bottom"
><A
HREF="c104.html"
ACCESSKEY="P"
>Prev</A
></TD
><TD
WIDTH="80%"
ALIGN="center"
VALIGN="bottom"
>Chapter 2. Advanced Usage</TD
><TD
WIDTH="10%"
ALIGN="right"
VALIGN="bottom"
><A
HREF="x148.html"
ACCESSKEY="N"
>Next</A
></TD
></TR
></TABLE
><HR
ALIGN="LEFT"
WIDTH="100%"></DIV
><DIV
CLASS="section"
><H1
CLASS="section"
><A
NAME="adv.design"
>2.2. Network Design</A
></H1
><P
> When creating a network it is necessary to define how many layers, neurons and connections it should have. If the network become too large, the ANN will
have difficulties learning and when it does learn it will tend to over-fit resulting in poor generalization. If the network becomes too small, it will
not be able to represent the rules needed to learn the problem and it will never gain a sufficiently low error rate.
</P
><P
> The number of hidden layers is also important. Generally speaking, if the problem is simple it is often enough to have one or two hidden layers, but as
the problems get more complex, so does the need for more layers.
</P
><P
> One way of getting a large network which is not too complex, is to adjust the connection_rate parameter given to
<A
HREF="r258.html"
><CODE
CLASS="function"
>fann_create</CODE
></A
>. If this parameter is 0.5, the constructed network will have the same amount of
neurons, but only half as many connections. It is difficult to say which problems this approach is useful for, but if you have a problem which can be
solved by a fully connected network, then it would be a good idea to see if it still works after removing half the connections.
</P
></DIV
><DIV
CLASS="NAVFOOTER"
><HR
ALIGN="LEFT"
WIDTH="100%"><TABLE
SUMMARY="Footer navigation table"
WIDTH="100%"
BORDER="0"
CELLPADDING="0"
CELLSPACING="0"
><TR
><TD
WIDTH="33%"
ALIGN="left"
VALIGN="top"
><A
HREF="c104.html"
ACCESSKEY="P"
>Prev</A
></TD
><TD
WIDTH="34%"
ALIGN="center"
VALIGN="top"
><A
HREF="index.html"
ACCESSKEY="H"
>Home</A
></TD
><TD
WIDTH="33%"
ALIGN="right"
VALIGN="top"
><A
HREF="x148.html"
ACCESSKEY="N"
>Next</A
></TD
></TR
><TR
><TD
WIDTH="33%"
ALIGN="left"
VALIGN="top"
>Advanced Usage</TD
><TD
WIDTH="34%"
ALIGN="center"
VALIGN="top"
><A
HREF="c104.html"
ACCESSKEY="U"
>Up</A
></TD
><TD
WIDTH="33%"
ALIGN="right"
VALIGN="top"
>Understanding the Error Value</TD
></TR
></TABLE
></DIV
></BODY
></HTML
>
|
By viewing downloads associated with this article you agree to the Terms of Service and the article's licence.
If a file you wish to view isn't highlighted, and is a text file (not binary), please
let us know and we'll add colourisation support for it.