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Morten Hjorth-Jensen
2024-11-25 08:12:27 +01:00
parent d63cb194d5
commit c8f2aa3dc1
181 changed files with 13447 additions and 2592 deletions
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doc/LectureNotes/_build/html/week46.html
+19 -14
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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">
@@ -693,13 +696,13 @@ predicting the target features of query instances is as follows:</p>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>2nd degree coefficients:
zero power: 1.391131752817723
first power: 0.023929544236763082
second power: -0.00011233101388608391
zero power: -9.690066070734556
first power: 0.2579633987876525
second power: -0.0008519856133366335
</pre></div>
</div>
<img alt="_images/54da4dcf618f83f729a4226ed97b89f907d17d25d6f1e00ebabeaabefc39c127.png" src="_images/54da4dcf618f83f729a4226ed97b89f907d17d25d6f1e00ebabeaabefc39c127.png" />
<img alt="_images/eb8a1d5930cd9fc5960f605b1df68a8d022a1f3d3f06c78dd6848a2fc9de92be.png" src="_images/eb8a1d5930cd9fc5960f605b1df68a8d022a1f3d3f06c78dd6848a2fc9de92be.png" />
<img alt="_images/8e8566a48272bbcd741d192ea8f10c53172ad3cba8f805ceb38c6695c7dd5c2d.png" src="_images/8e8566a48272bbcd741d192ea8f10c53172ad3cba8f805ceb38c6695c7dd5c2d.png" />
<img alt="_images/eb601133698cb5198be6ed45531c33666c9fa7198b8b8a8e59f3cf4e95ddc8eb.png" src="_images/eb601133698cb5198be6ed45531c33666c9fa7198b8b8a8e59f3cf4e95ddc8eb.png" />
</div>
</div>
</section>
@@ -2184,7 +2187,9 @@ SVC 0.896
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>LogisticRegression 0.864
RandomForestClassifier 0.896
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>RandomForestClassifier 0.896
SVC 0.896
</pre></div>
</div>
@@ -2302,7 +2307,9 @@ Error: 0.06380941468319971
Bias^2: 0.05160313473529168
Var: 0.01220627994790804
0.06380941468319971 &gt;= 0.05160313473529168 + 0.01220627994790804 = 0.06380941468319971
Polynomial degree: 2
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Polynomial degree: 2
Error: 0.043464037468677004
Bias^2: 0.02659851591375224
Var: 0.01686552155492476
@@ -2312,9 +2319,7 @@ Error: 0.020716391693769383
Bias^2: 0.01159033914386312
Var: 0.00912605254990626
0.020716391693769383 &gt;= 0.01159033914386312 + 0.00912605254990626 = 0.02071639169376938
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Polynomial degree: 4
Polynomial degree: 4
Error: 0.02063627410934057
Bias^2: 0.0117496656370668
Var: 0.008886608472273775
@@ -2324,7 +2329,9 @@ Error: 0.02087627881701288
Bias^2: 0.01349183949256158
Var: 0.007384439324451296
0.02087627881701288 &gt;= 0.01349183949256158 + 0.007384439324451296 = 0.020876278817012876
Polynomial degree: 6
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Polynomial degree: 6
Error: 0.02069601123831537
Bias^2: 0.013918526350129823
Var: 0.0067774848881855445
@@ -2463,9 +2470,7 @@ this setting.</p>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>(426, 30)
(143, 30)
Test set accuracy Logistic Regression with scaled data: 0.96
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Test set accuracy SVM with scaled data: 0.96
Test set accuracy SVM with scaled data: 0.96
Test set accuracy with Decision Trees and scaled data: 0.87
</pre></div>
</div>