File:Error surface of a linear neuron for a single training case.png

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Error_surface_of_a_linear_neuron_for_a_single_training_case.png (468 × 372 pixels, file size: 7 KB, MIME type: image/png)

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Summary

Description
English: On the x-axis is the output, y, of a linear neuron and on the y-axis is the error, E, of the output compared to a target output of zero. The error is calculated by squaring the difference between the actual and target output. This demonstrates that training of a neural network can be thought of as an optimization problem where the correct output involves finding the minima of the parabola.
Date
Source Own work
Author AI456
PNG development
InfoField
 This diagram was created with MATLAB.

Source code

function [output] = Plot_Error_Surface(x, expected)
% Plots the error surface for a single output unit with the given
% expected output.
hold all
for e = expected
   y = (e - x).^2; 
   plot(x, y)
   grid on 
   title ('Error Surface for a Single Training Case');
   xlabel('y')
   ylabel('E')
end
hold off

Plot_Error_Surface(-5:0.5:5, 0)

Licensing

I, the copyright holder of this work, hereby publish it under the following licenses:
GNU head Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License.
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12 February 2013

6,800 byte

372 pixel

468 pixel

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15dabb5d3513a2d0c97a96a36659e7a17740011e

File history

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Date/TimeThumbnailDimensionsUserComment
current16:43, 12 February 2013Thumbnail for version as of 16:43, 12 February 2013468 × 372 (7 KB)wikimediacommons>AI456{{subst:Upload marker added by en.wp UW}} {{Information |Description = {{en|On the x-axis is the output, y, of a linear neuron and on the y-axis is the error, E, of the output compared to a target output of zero. The error is calculated by squaring the...

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