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Morten Hjorth-Jensen
2023-11-08 15:57:33 +01:00
parent 2edd177646
commit 3b9f0dbb29
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doc/LectureNotes/_build/html/week35.html
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@@ -343,6 +343,16 @@ const thebe_selector_output = ".output, .cell_output"
Week 43: Deep Learning: Constructing a Neural Network code and solving differential equations
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="week44.html">
Week 44, Convolutional Neural Networks (CNN)
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="week45.html">
Week 45, Recurrent Neural Networks
</a>
</li>
</ul>
<p aria-level="2" class="caption" role="heading">
<span class="caption-text">
@@ -1706,7 +1716,7 @@ Since we are not using <strong>Scikit-Learn</strong> here we can define our own
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.9955273625597437
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.996738628265756
</pre></div>
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@@ -1723,7 +1733,7 @@ Since we are not using <strong>Scikit-Learn</strong> here we can define our own
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<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.008900933315885705
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.00846262916105675
</pre></div>
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@@ -1738,23 +1748,31 @@ Since we are not using <strong>Scikit-Learn</strong> here we can define our own
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<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[0.00643899 0.04246989 0.0607062 0.02997344 0.0011878 0.00123457
0.00324986 0.03285652 0.01028728 0.01571866 0.03940381 0.0814985
0.038844 0.01828593 0.03967758 0.00303693 0.02227466 0.02702328
0.00026861 0.00883798 0.02876697 0.00472251 0.03141454 0.02911162
0.02387339 0.00585113 0.00110716 0.00587564 0.00693821 0.00604105
0.00804985 0.02058094 0.01151984 0.01782721 0.0286851 0.08874631
0.01678538 0.0065912 0.03611471 0.02706508 0.00313125 0.04977093
0.00415289 0.02760079 0.00518122 0.00628874 0.00739489 0.01619456
0.00996972 0.02210753 0.02030107 0.02100763 0.04699527 0.01512934
0.00717079 0.01784714 0.01095703 0.01281486 0.0231703 0.04482932
0.00287871 0.0565419 0.04028659 0.03102525 0.01617722 0.0271761
0.01736502 0.03394827 0.00328494 0.05750876 0.0059888 0.01915888
0.01423609 0.01024227 0.03660869 0.01012951 0.00534938 0.03375068
0.02699539 0.04083439 0.04965227 0.00565625 0.02250553 0.00893027
0.02244755 0.00741987 0.00189101 0.02042476 0.02036545 0.06362348
0.03145163 0.02987833 0.07393685 0.0033575 0.02791218 0.00214832
0.0111154 0.01344581 0.00368581 0.01436601]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[2.18321314e-02 4.63790586e-02 1.86599003e-02 2.57537966e-02
7.75301638e-03 2.41708096e-03 2.05388549e-02 2.24797183e-02
3.80669838e-02 1.77124395e-02 5.74437617e-02 8.91992985e-03
3.79831624e-02 1.33444711e-02 2.46753261e-02 2.04450975e-02
8.98180203e-02 1.21522960e-02 3.12747234e-03 1.31395784e-03
1.84447599e-03 2.96525482e-03 6.28909679e-03 1.52006777e-02
2.87135280e-03 2.40513177e-02 3.35417405e-02 5.92991719e-03
3.54379087e-02 7.18303628e-03 1.54601264e-02 2.15148810e-02
2.79754897e-03 4.12602928e-03 4.22227163e-02 3.09676156e-02
1.25713219e-02 2.32108713e-02 2.44657526e-02 1.05066388e-02
6.68324974e-02 2.97565845e-02 2.42484290e-02 1.89707309e-02
2.19461919e-02 1.41644629e-02 1.41226929e-02 5.23396766e-03
3.21530495e-03 3.66036618e-03 7.91408373e-03 3.18065689e-02
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8.94501598e-03 4.64365518e-03 4.55438359e-02 3.34347894e-03
4.97761429e-03 2.71875845e-02 1.57316402e-02 4.15628391e-02
4.75979803e-02 8.77079389e-03 3.22623101e-03 2.53596681e-03
4.02206965e-02 3.06020683e-02 3.07080407e-02 9.75525377e-03
6.45380691e-02 2.66174067e-02 1.94727053e-03 4.82766482e-03
3.39313789e-03 5.00126617e-02 3.25794223e-02 3.97663980e-02
3.51267283e-02 4.43226747e-02 4.45976616e-03 2.86750237e-02
2.33197004e-02 9.78449688e-05 4.38688646e-02 2.86830766e-02
2.90763970e-02 9.24053124e-03 1.36970119e-02 6.97177697e-02
2.34728094e-02 2.31728952e-02 3.08484802e-03 6.25254477e-02]
</pre></div>
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@@ -1823,15 +1841,15 @@ but now splitting the data into a training set and a test set.</p>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[ 2.09851217 -1.48209629 10.27096183 -6.79998516 2.87206824]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[ 1.97864285 0.28134042 4.70594499 -0.58368727 0.70917314]
Training R2
0.9957273060382023
0.993658072083743
Training MSE
0.010053880703541525
0.012874822204495243
Test R2
0.9888005551376943
0.9945729062189713
Test MSE
0.008043926731954223
0.007472516848671787
</pre></div>
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