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<a href="Bio-module.html">Package Bio</a> ::
<a href="Bio.NeuralNetwork-module.html">Package NeuralNetwork</a> ::
<a href="Bio.NeuralNetwork.StopTraining-module.html">Module StopTraining</a> ::
Class ValidationIncreaseStop
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<!-- ==================== CLASS DESCRIPTION ==================== -->
<h1 class="epydoc">Class ValidationIncreaseStop</h1><p class="nomargin-top"><span class="codelink"><a href="Bio.NeuralNetwork.StopTraining-pysrc.html#ValidationIncreaseStop">source code</a></span></p>
<p>Class to stop training on a network when the validation error
increases.</p>
<p>Normally, during training of a network, the error will always decrease
on the set of data used in the training. However, if an independent set
of data is used for validation, the error will decrease to a point, and
then start to increase. This increase normally occurs due to the fact
that the network is starting to learn noise in the training data set.
This stopping criterion function will stop when the validation error
increases.</p>
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<td><span class="summary-sig"><a href="Bio.NeuralNetwork.StopTraining.ValidationIncreaseStop-class.html#__init__" class="summary-sig-name">__init__</a>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">max_iterations</span>=<span class="summary-sig-default">None</span>,
<span class="summary-sig-arg">min_iterations</span>=<span class="summary-sig-default">0</span>,
<span class="summary-sig-arg">verbose</span>=<span class="summary-sig-default">0</span>)</span><br />
Initialize the stopping criterion class.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.StopTraining-pysrc.html#ValidationIncreaseStop.__init__">source code</a></span>
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<td><span class="summary-sig"><a name="stopping_criteria"></a><span class="summary-sig-name">stopping_criteria</span>(<span class="summary-sig-arg">self</span>,
<span class="summary-sig-arg">num_iterations</span>,
<span class="summary-sig-arg">training_error</span>,
<span class="summary-sig-arg">validation_error</span>)</span><br />
Define when to stop iterating.</td>
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<span class="codelink"><a href="Bio.NeuralNetwork.StopTraining-pysrc.html#ValidationIncreaseStop.stopping_criteria">source code</a></span>
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<h3 class="epydoc"><span class="sig"><span class="sig-name">__init__</span>(<span class="sig-arg">self</span>,
<span class="sig-arg">max_iterations</span>=<span class="sig-default">None</span>,
<span class="sig-arg">min_iterations</span>=<span class="sig-default">0</span>,
<span class="sig-arg">verbose</span>=<span class="sig-default">0</span>)</span>
<br /><em class="fname">(Constructor)</em>
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</td><td align="right" valign="top"
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<p>Initialize the stopping criterion class.</p>
<p>Arguments:</p>
<p>o max_iterations - The maximum number of iterations that should be
performed, regardless of error.</p>
<p>o min_iterations - The minimum number of iterations to perform, to
prevent premature stoppage of training.</p>
<p>o verbose - Whether or not the error should be printed during
training.</p>
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