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models-mse.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8"/>
<title>MSE - Deep.Net</title>
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<ul class="nav nav-pills pull-right">
<li><a href="http://github.com/DeepMLNet/DeepNet">github page</a></li>
</ul>
<h3 class="muted"><a href="http://www.deepml.net/index.html">Deep.Net</a></h3>
</div>
<hr />
<div class="row">
<div class="span9" id="main">
<h1>MSE</h1>
<p>
<span>Namespace: Models</span><br />
</p>
<div class="xmldoc">
<p>Mean over samples of squared error.</p>
</div>
<!-- Render nested types and modules, if there are any -->
<h3>Functions and values</h3>
<table class="table table-bordered member-list">
<thead>
<tr><td>Function or value</td><td>Description</td></tr>
</thead>
<tbody>
<tr>
<td class="member-name">
<code onmouseout="hideTip(event, '68', 68)" onmouseover="showTip(event, '68', 68)">
error trgt pred
</code>
<div class="tip" id="68">
<strong>Signature:</strong> trgt:Tensor<'T> -> pred:Tensor<'T> -> float<br />
<strong>Type parameters:</strong> 'T </div>
</td>
<td class="xmldoc">
<a href="http://github.com/DeepMLNet/DeepNet/tree/master/MLModels/Quality.fs#L60-60" class="github-link">
<img src="../content/img/github.png" class="normal" />
<img src="../content/img/github-blue.png" class="hover" />
</a>
<p>Calculates the mean squared error.
The mean is taken over the samples. The error is summed over all
other dimensions.
Shapes: pred[smpl, ...], target[smpl, ...]</p>
</td>
</tr>
<tr>
<td class="member-name">
<code onmouseout="hideTip(event, '69', 69)" onmouseover="showTip(event, '69', 69)">
ofPredictor (...)
</code>
<div class="tip" id="69">
<strong>Signature:</strong> dataset:TrnValTst<'S> -> batchSize:int64 -> trgtFn:('S -> Tensor<'T>) -> predFn:('S -> Tensor<'T>) -> float * float * float<br />
<strong>Type parameters:</strong> 'S, 'T </div>
</td>
<td class="xmldoc">
<a href="http://github.com/DeepMLNet/DeepNet/tree/master/MLModels/Quality.fs#L64-64" class="github-link">
<img src="../content/img/github.png" class="normal" />
<img src="../content/img/github-blue.png" class="hover" />
</a>
<p>Calculates the MSE of a predictor on the training, validation and test sets.</p>
</td>
</tr>
</tbody>
</table>
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