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Morten Hjorth-Jensen
2024-11-25 08:12:27 +01:00
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commit c8f2aa3dc1
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doc/LectureNotes/_build/html/week44.html
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@@ -257,6 +257,9 @@
<li class="toctree-l1"><a class="reference internal" href="week47.html">Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods</a></li>
<li class="toctree-l1"><a class="reference internal" href="exercisesweek47.html">Exercise week 47</a></li>
<li class="toctree-l1"><a class="reference internal" href="week48.html">Week 48: Gradient boosting and summary of course</a></li>
<li class="toctree-l1"><a class="reference internal" href="exercisesweek48.html">Exercises week 48</a></li>
</ul>
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Projects</span></p>
<ul class="nav bd-sidenav">
@@ -1574,40 +1577,24 @@ labels = (n_inputs) = (1797,)
super().__init__(activity_regularizer=activity_regularizer, **kwargs)
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><span class=" -Color -Color-Bold"> 1/12</span> <span class=" -Color -Color-Green">━</span><span class=" -Color -Color-White">━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">1s</span> 131ms/step - accuracy: 0.0938 - loss: 3.2865
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><span class=" -Color -Color-Bold"> 1/12</span> <span class=" -Color -Color-Green">━</span><span class=" -Color -Color-White">━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">1s</span> 176ms/step - accuracy: 0.0625 - loss: 2.4493
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<span class=" -Color -Color-Bold"> 9/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━</span><span class=" -Color -Color-White">━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 7ms/step - accuracy: 0.1090 - loss: 3.1259
<span class=" -Color -Color-Bold"> 8/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━</span><span class=" -Color -Color-White">━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 8ms/step - accuracy: 0.1149 - loss: 2.4557
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<span class=" -Color -Color-Bold">12/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 9ms/step - accuracy: 0.1140 - loss: 3.1040
<span class=" -Color -Color-Bold">12/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 31ms/step - accuracy: 0.1176 - loss: 2.4545
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<span class=" -Color -Color-Bold">12/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">1s</span> 32ms/step - accuracy: 0.1184 - loss: 2.4540
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Learning rate = 1e-05
Lambda = 1e-05
Test accuracy: 0.125
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><span class=" -Color -Color-Bold"> 1/12</span> <span class=" -Color -Color-Green">━</span><span class=" -Color -Color-White">━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">1s</span> 133ms/step - accuracy: 0.2812 - loss: 2.6529
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<span class=" -Color -Color-Bold"> 8/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━</span><span class=" -Color -Color-White">━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 7ms/step - accuracy: 0.2350 - loss: 2.5504
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<span class=" -Color -Color-Bold">12/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 9ms/step - accuracy: 0.2247 - loss: 2.5413
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<span class=" -Color -Color-Bold">12/12</span> <span class=" -Color -Color-Green">━━━━━━━━━━━━━━━━━━━━</span> <span class=" -Color -Color-Bold">0s</span> 10ms/step - accuracy: 0.2230 - loss: 2.5413
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Learning rate = 1e-05
Lambda = 0.0001
Test accuracy: 0.203
Test accuracy: 0.128
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