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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/chapter2.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">
@@ -1185,10 +1188,10 @@ covariance matrix through the <strong>np.linalg.eig()</strong> function.</p>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.07163028969289174
3.7656278764040367
[[0.7647107 2.29986727]
[2.29986727 7.88107866]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.00239782448350092
3.945643027765946
[[1.04582521 3.00214849]
[3.00214849 9.76163974]]
</pre></div>
</div>
</div>
@@ -1225,10 +1228,10 @@ a more brute force way. Here we scale the mean values for each column of the des
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.08212703190343323
2.425866065899094
[[1. 0.65333306]
[0.65333306 1. ]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.07878080847813602
2.1500369042116563
[[1. 0.63295205]
[0.63295205 1. ]]
</pre></div>
</div>
</div>
@@ -1258,30 +1261,30 @@ this matrix we easily see that it is a positive definite matrix.</p>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[-0.68481734 -2.74241828]
[-1.03710525 -3.82202137]
[ 0.71505805 2.54840587]
[ 0.4645853 0.98764188]
[-1.95392781 -4.51089358]
[ 0.79256149 3.37757489]
[-0.18745641 0.4457749 ]
[ 2.53950612 7.87543978]
[ 0.25354074 -0.28008123]
[-0.90194489 -3.87942287]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[-0.05862476 0.45533295]
[ 0.84689611 4.01381445]
[ 0.21778772 0.62032544]
[-1.3117471 -2.69182187]
[-0.78512935 -3.44198948]
[-0.12030798 -0.93994208]
[ 0.60559053 2.2457079 ]
[ 1.8170149 4.51652722]
[-0.44215901 -3.25646952]
[-0.76932106 -1.52148501]]
0 1
0 -0.684817 -2.742418
1 -1.037105 -3.822021
2 0.715058 2.548406
3 0.464585 0.987642
4 -1.953928 -4.510894
5 0.792561 3.377575
6 -0.187456 0.445775
7 2.539506 7.875440
8 0.253541 -0.280081
9 -0.901945 -3.879423
0 1
0 1.000000 0.972082
1 0.972082 1.000000
0 -0.058625 0.455333
1 0.846896 4.013814
2 0.217788 0.620325
3 -1.311747 -2.691822
4 -0.785129 -3.441989
5 -0.120308 -0.939942
6 0.605591 2.245708
7 1.817015 4.516527
8 -0.442159 -3.256470
9 -0.769321 -1.521485
0 1
0 1.00000 0.92403
1 0.92403 1.00000
</pre></div>
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</div>
@@ -1338,37 +1341,37 @@ this matrix we easily see that it is a positive definite matrix.</p>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span> 0 1 2 3 4 5 6 7 \
0 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
1 0.0 0.070253 0.070611 0.070163 0.068562 0.067004 0.062136 0.060528
2 0.0 0.070611 0.071502 0.070808 0.069529 0.068256 0.062916 0.061526
3 0.0 0.070163 0.070808 0.074767 0.073368 0.071996 0.069069 0.067536
4 0.0 0.068562 0.069529 0.073368 0.072239 0.071113 0.068033 0.066707
5 0.0 0.067004 0.068256 0.071996 0.071113 0.070210 0.067007 0.065872
6 0.0 0.062136 0.062916 0.069069 0.068033 0.067007 0.065727 0.064490
7 0.0 0.060528 0.061526 0.067536 0.066707 0.065872 0.064490 0.063421
8 0.0 0.059023 0.060216 0.066097 0.065457 0.064796 0.063327 0.062411
9 0.0 0.057616 0.058984 0.064749 0.064281 0.063778 0.062233 0.061458
10 0.0 0.054096 0.054970 0.061945 0.061234 0.060520 0.060261 0.059314
11 0.0 0.052750 0.053781 0.060606 0.060054 0.059486 0.059137 0.058322
12 0.0 0.051499 0.052672 0.059359 0.058952 0.058518 0.058088 0.057394
13 0.0 0.050336 0.051637 0.058198 0.057923 0.057612 0.057109 0.056526
14 0.0 0.049255 0.050672 0.057116 0.056962 0.056764 0.056195 0.055714
1 0.0 0.081622 0.081406 0.078296 0.079396 0.080527 0.068235 0.069327
2 0.0 0.081406 0.081919 0.078612 0.080089 0.081603 0.068822 0.070146
3 0.0 0.078296 0.078612 0.080411 0.081717 0.083038 0.073368 0.074578
4 0.0 0.079396 0.080089 0.081717 0.083265 0.084831 0.074620 0.075994
5 0.0 0.080527 0.081603 0.083038 0.084831 0.086645 0.075870 0.077411
6 0.0 0.068235 0.068822 0.073368 0.074620 0.075870 0.069194 0.070300
7 0.0 0.069327 0.070146 0.074578 0.075994 0.077411 0.070300 0.071523
8 0.0 0.070483 0.071536 0.075839 0.077423 0.079011 0.071441 0.072784
9 0.0 0.071702 0.072994 0.077153 0.078908 0.080672 0.072619 0.074087
10 0.0 0.059187 0.059821 0.065770 0.066863 0.067945 0.063580 0.064519
11 0.0 0.060114 0.060903 0.066767 0.067977 0.069178 0.064472 0.065498
12 0.0 0.061096 0.062042 0.067812 0.069142 0.070466 0.065402 0.066517
13 0.0 0.062134 0.063240 0.068908 0.070362 0.071812 0.066371 0.067578
14 0.0 0.063230 0.064502 0.070057 0.071639 0.073220 0.067381 0.068684
8 9 10 11 12 13 14
0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
1 0.059023 0.057616 0.054096 0.052750 0.051499 0.050336 0.049255
2 0.060216 0.058984 0.054970 0.053781 0.052672 0.051637 0.050672
3 0.066097 0.064749 0.061945 0.060606 0.059359 0.058198 0.057116
4 0.065457 0.064281 0.061234 0.060054 0.058952 0.057923 0.056962
5 0.064796 0.063778 0.060520 0.059486 0.058518 0.057612 0.056764
6 0.063327 0.062233 0.060261 0.059137 0.058088 0.057109 0.056195
7 0.062411 0.061458 0.059314 0.058322 0.057394 0.056526 0.055714
8 0.061541 0.060718 0.058420 0.057549 0.056732 0.055967 0.055250
9 0.060718 0.060014 0.057576 0.056817 0.056103 0.055433 0.054805
10 0.058420 0.057576 0.056198 0.055300 0.054459 0.053671 0.052934
11 0.057549 0.056817 0.055300 0.054507 0.053763 0.053066 0.052412
12 0.056732 0.056103 0.054459 0.053763 0.053109 0.052495 0.051918
13 0.055967 0.055433 0.053671 0.053066 0.052495 0.051957 0.051452
14 0.055250 0.054805 0.052934 0.052412 0.051918 0.051452 0.051015
1 0.070483 0.071702 0.059187 0.060114 0.061096 0.062134 0.063230
2 0.071536 0.072994 0.059821 0.060903 0.062042 0.063240 0.064502
3 0.075839 0.077153 0.065770 0.066767 0.067812 0.068908 0.070057
4 0.077423 0.078908 0.066863 0.067977 0.069142 0.070362 0.071639
5 0.079011 0.080672 0.067945 0.069178 0.070466 0.071812 0.073220
6 0.071441 0.072619 0.063580 0.064472 0.065402 0.066371 0.067381
7 0.072784 0.074087 0.064519 0.065498 0.066517 0.067578 0.068684
8 0.074170 0.075601 0.065481 0.066550 0.067660 0.068817 0.070021
9 0.075601 0.077163 0.066469 0.067629 0.068835 0.070089 0.071396
10 0.065481 0.066469 0.059543 0.060291 0.061066 0.061870 0.062705
11 0.066550 0.067629 0.060291 0.061104 0.061946 0.062820 0.063728
12 0.067660 0.068835 0.061066 0.061946 0.062859 0.063805 0.064788
13 0.068817 0.070089 0.061870 0.062820 0.063805 0.064827 0.065887
14 0.070021 0.071396 0.062705 0.063728 0.064788 0.065887 0.067030
</pre></div>
</div>
</div>