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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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 Created using MatLab
Author AI456

Source code

[edit]
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

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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.
w:en:Creative Commons
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This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
You are free:
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Under the following conditions:
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Date/TimeThumbnailDimensionsUserComment
current15:43, 12 February 2013Thumbnail for version as of 15:43, 12 February 2013468 × 372 (7 KB)AI456 (talk | contribs){{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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