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Practical Neural Network Recipies in C++
book

Practical Neural Network Recipies in C++

by Masters
June 2014
Intermediate to advanced content levelIntermediate to advanced
493 pages
20h 30m
English
Morgan Kaufmann
Content preview from Practical Neural Network Recipies in C++
64
Chapter 4
Measuring Prediction Error
Suppose that we have trained a neural network to do time-series
prediction. We have a test series with which to evaluate the perfor-
mance of the trained network. Using groups of known points from the
test series, we make predictions. For each prediction, we know the
value of the series as predicted by the network, and we know the true
value of the series. The problem now is to express the performance of
the network in a useful manner.
Most neural network training algorithms work by minimizing
the mean square error of the output(s). Naturally, during training this
is done in terms of the scaled data tha ...
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Publisher Resources

ISBN: 9780080514338