<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <HTML ><HEAD ><TITLE >Understanding the Error Value</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="Network Design" HREF="x141.html"><LINK REL="NEXT" TITLE="Training and Testing" HREF="x161.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="x141.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="x161.html" ACCESSKEY="N" >Next</A ></TD ></TR ></TABLE ><HR ALIGN="LEFT" WIDTH="100%"></DIV ><DIV CLASS="section" ><H1 CLASS="section" ><A NAME="adv.errval" >2.3. Understanding the Error Value</A ></H1 ><P > The mean square error value is calculated while the ANN is being trained. Some functions are implemented, to use and manipulate this error value. The <A HREF="r577.html" ><CODE CLASS="function" >fann_get_MSE</CODE ></A > function returns the error value and the <A HREF="r593.html" ><CODE CLASS="function" >fann_reset_MSE</CODE ></A > resets the error value. The following explains how the mean square error value is calculated, to give an idea of the value's ability to reveal the quality of the training. </P ><P > If <SPAN CLASS="emphasis" ><I CLASS="emphasis" >d</I ></SPAN > is the desired output of an output neuron and <SPAN CLASS="emphasis" ><I CLASS="emphasis" >y</I ></SPAN > is the actual output of the neuron, the square error is (d - y) squared. If two output neurons exists, then the mean square error for these two neurons is the average of the two square errors. </P ><P > When training with the <A HREF="r806.html" ><CODE CLASS="function" >fann_train_on_file</CODE ></A > function, an error value is printed. This error value is the mean square error for all the training data. Meaning that it is the average of all the square errors in each of the training pairs. </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="x141.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="x161.html" ACCESSKEY="N" >Next</A ></TD ></TR ><TR ><TD WIDTH="33%" ALIGN="left" VALIGN="top" >Network Design</TD ><TD WIDTH="34%" ALIGN="center" VALIGN="top" ><A HREF="c104.html" ACCESSKEY="U" >Up</A ></TD ><TD WIDTH="33%" ALIGN="right" VALIGN="top" >Training and Testing</TD ></TR ></TABLE ></DIV ></BODY ></HTML >
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