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Morten Hjorth-Jensen
2023-11-21 06:16:54 +01:00
parent a854a3e9c0
commit 06b09eb681
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@@ -353,6 +353,16 @@ const thebe_selector_output = ".output, .cell_output"
Week 45, Recurrent Neural Networks
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</li>
<li class="toctree-l1">
<a class="reference internal" href="week46.html">
Week 46: Decision Trees, Ensemble methods and Random Forests
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<li class="toctree-l1">
<a class="reference internal" href="week47.html">
Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods and Summary of Course
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@@ -367,7 +377,12 @@ const thebe_selector_output = ".output, .cell_output"
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<li class="toctree-l1">
<a class="reference internal" href="project2.html">
Project 2 on Machine Learning, deadline November 13 (Midnight)
Project 2 on Machine Learning, deadline November 17 (Midnight)
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="project3.html">
Project 3 on Machine Learning, deadline December 18 (midnight), 2023
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</li>
</ul>
@@ -1317,7 +1332,27 @@ labels = (n_inputs) = (1797,)
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/keras/optimizer_v2/gradient_descent.py:102: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.
super(SGD, self).__init__(name, **kwargs)
2023-11-08 15:24:42.293245: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
2023-11-21 06:09:14.627153: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span> 1/12 [=&gt;............................] - ETA: 1s - loss: 2.5762 - accuracy: 0.2188
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>
7/12 [================&gt;.............] - ETA: 0s - loss: 2.7312 - accuracy: 0.2277
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>
12/12 [==============================] - ETA: 0s - loss: 2.7089 - accuracy: 0.2389
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>
12/12 [==============================] - 1s 35ms/step - loss: 2.7089 - accuracy: 0.2389
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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: 0.239
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<div class="output traceback highlight-ipythontb notranslate"><div class="highlight"><pre><span></span><span class="gt">---------------------------------------------------------------------------</span>