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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)

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 Created using MatLab
Author AI456

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)

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Date/TimeThumbnailDimensionsUserComment
current15:43, 12 February 2013Thumbnail for version as of 15:43, 12 February 2013468 × 372 (7 KB)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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