update
This commit is contained in:
Morten Hjorth-Jensen
@@ -353,6 +353,16 @@ const thebe_selector_output = ".output, .cell_output"
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Week 45, Recurrent Neural Networks
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</a>
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</li>
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<li class="toctree-l1">
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<a class="reference internal" href="week46.html">
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Week 46: Decision Trees, Ensemble methods and Random Forests
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</a>
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</li>
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<li class="toctree-l1">
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<a class="reference internal" href="week47.html">
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Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods and Summary of Course
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</a>
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</li>
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</ul>
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<p aria-level="2" class="caption" role="heading">
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<span class="caption-text">
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@@ -367,7 +377,12 @@ const thebe_selector_output = ".output, .cell_output"
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</li>
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<li class="toctree-l1">
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<a class="reference internal" href="project2.html">
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Project 2 on Machine Learning, deadline November 13 (Midnight)
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Project 2 on Machine Learning, deadline November 17 (Midnight)
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</a>
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</li>
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<li class="toctree-l1">
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<a class="reference internal" href="project3.html">
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Project 3 on Machine Learning, deadline December 18 (midnight), 2023
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</a>
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</li>
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</ul>
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@@ -1335,10 +1350,10 @@ covariance matrix through the <strong>np.linalg.eig()</strong> function.</p>
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</div>
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</div>
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<div class="cell_output docutils container">
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.07752620206774397
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4.3068687590657415
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[[1.01031184 2.85759522]
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[2.85759522 9.0542566 ]]
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.031405320178937886
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3.7508636683863235
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[[ 1.07728714 3.41235715]
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[ 3.41235715 11.76274779]]
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</pre></div>
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</div>
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</div>
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@@ -1375,10 +1390,10 @@ a more brute force way. Here we scale the mean values for each column of the des
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</div>
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</div>
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<div class="cell_output docutils container">
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.07472152457534222
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1.4560786541572335
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[[1. 0.61219726]
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[0.61219726 1. ]]
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.08460107110703337
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1.9541100061668464
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[[1. 0.73391309]
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[0.73391309 1. ]]
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</pre></div>
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</div>
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</div>
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@@ -1408,30 +1423,30 @@ this matrix we easily see that it is a positive definite matrix.</p>
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</div>
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</div>
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<div class="cell_output docutils container">
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[-0.59265811 -0.57943748]
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[ 0.08641073 0.06656566]
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[-0.68596176 -2.59060904]
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[ 0.47558206 1.64482901]
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[ 0.21597684 -0.67723533]
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[ 1.22935165 5.02293408]
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[-0.51249881 -3.38478181]
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[ 0.29220202 1.35149796]
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[ 0.10955639 0.86177342]
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[-0.61796102 -1.71553646]]
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[-0.80226723 -3.04272582]
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[ 0.43201921 2.14816084]
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[ 1.57309147 3.36212275]
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[-1.88172029 -7.76015446]
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[ 1.07203435 4.92153252]
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[ 0.60376519 3.40447029]
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[-0.63613568 -1.37836163]
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[-1.93626155 -5.91514067]
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[ 1.59593425 4.28910504]
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[-0.02045972 -0.02900886]]
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0 1
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0 -0.592658 -0.579437
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1 0.086411 0.066566
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2 -0.685962 -2.590609
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3 0.475582 1.644829
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4 0.215977 -0.677235
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5 1.229352 5.022934
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6 -0.512499 -3.384782
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7 0.292202 1.351498
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8 0.109556 0.861773
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9 -0.617961 -1.715536
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0 -0.802267 -3.042726
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1 0.432019 2.148161
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2 1.573091 3.362123
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3 -1.881720 -7.760154
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4 1.072034 4.921533
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5 0.603765 3.404470
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6 -0.636136 -1.378362
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7 -1.936262 -5.915141
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8 1.595934 4.289105
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9 -0.020460 -0.029009
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0 1
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0 1.000000 0.921567
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1 0.921567 1.000000
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0 1.000000 0.965295
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1 0.965295 1.000000
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</pre></div>
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</div>
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</div>
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@@ -1488,37 +1503,40 @@ this matrix we easily see that it is a positive definite matrix.</p>
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<div class="cell_output docutils container">
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span> 0 1 2 3 4 5 6 7 \
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0 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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1 0.0 0.079330 0.084471 0.080541 0.081753 0.082306 0.073011 0.072990
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2 0.0 0.084471 0.092487 0.087280 0.089513 0.090777 0.079391 0.079777
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3 0.0 0.080541 0.087280 0.087211 0.088900 0.089752 0.082231 0.082329
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4 0.0 0.081753 0.089513 0.088900 0.091023 0.092206 0.083848 0.084164
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5 0.0 0.082306 0.090777 0.089752 0.092206 0.093657 0.084672 0.085172
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6 0.0 0.073011 0.079391 0.082231 0.083848 0.084672 0.079611 0.079715
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7 0.0 0.072990 0.079777 0.082329 0.084164 0.085172 0.079715 0.079958
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8 0.0 0.072802 0.079892 0.082196 0.084212 0.085382 0.079597 0.079964
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9 0.0 0.072527 0.079854 0.081937 0.084110 0.085425 0.079353 0.079836
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10 0.0 0.064985 0.070571 0.075171 0.076586 0.077304 0.074181 0.074265
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11 0.0 0.064627 0.070400 0.074809 0.076355 0.077194 0.073842 0.074026
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12 0.0 0.064245 0.070170 0.074403 0.076066 0.077017 0.073458 0.073736
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13 0.0 0.063864 0.069919 0.073987 0.075758 0.076814 0.073063 0.073431
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14 0.0 0.063500 0.069672 0.073582 0.075454 0.076612 0.072676 0.073131
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1 0.0 0.090537 0.085374 0.090091 0.089893 0.089356 0.080696 0.081199
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2 0.0 0.085374 0.081563 0.083636 0.083982 0.084114 0.074319 0.075079
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3 0.0 0.090091 0.083636 0.094993 0.094026 0.092598 0.088156 0.088323
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4 0.0 0.089893 0.083982 0.094026 0.093386 0.092327 0.086892 0.087259
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5 0.0 0.089356 0.084114 0.092598 0.092327 0.091697 0.085163 0.085746
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6 0.0 0.080696 0.074319 0.088156 0.086892 0.085163 0.083797 0.083762
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7 0.0 0.081199 0.075079 0.088323 0.087259 0.085746 0.083762 0.083873
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8 0.0 0.081680 0.075858 0.088410 0.087566 0.086291 0.083628 0.083894
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9 0.0 0.082105 0.076636 0.088369 0.087768 0.086762 0.083348 0.083777
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10 0.0 0.071274 0.065396 0.079741 0.078433 0.076697 0.077121 0.077004
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11 0.0 0.071854 0.066119 0.080197 0.079026 0.077431 0.077466 0.077460
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12 0.0 0.072470 0.066891 0.080665 0.079640 0.078196 0.077810 0.077920
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13 0.0 0.073113 0.067709 0.081133 0.080262 0.078981 0.078139 0.078370
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14 0.0 0.073773 0.068568 0.081581 0.080878 0.079775 0.078433 0.078791
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8 9 10 11 12 13 14
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0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
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1 0.072802 0.072527 0.064985 0.064627 0.064245 0.063864 0.063500
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2 0.079892 0.079854 0.070571 0.070400 0.070170 0.069919 0.069672
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3 0.082196 0.081937 0.075171 0.074809 0.074403 0.073987 0.073582
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4 0.084212 0.084110 0.076586 0.076355 0.076066 0.075758 0.075454
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5 0.085382 0.085425 0.077304 0.077194 0.077017 0.076814 0.076612
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6 0.079597 0.079353 0.074181 0.073842 0.073458 0.073063 0.072676
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7 0.079964 0.079836 0.074265 0.074026 0.073736 0.073431 0.073131
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8 0.080086 0.080069 0.074152 0.074008 0.073810 0.073592 0.073378
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9 0.080069 0.080157 0.073929 0.073876 0.073766 0.073635 0.073504
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10 0.074152 0.073929 0.070129 0.069821 0.069475 0.069119 0.068771
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11 0.074008 0.073876 0.069821 0.069595 0.069327 0.069048 0.068774
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12 0.073810 0.073766 0.069475 0.069327 0.069136 0.068931 0.068731
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13 0.073592 0.073635 0.069119 0.069048 0.068931 0.068800 0.068671
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14 0.073378 0.073504 0.068771 0.068774 0.068731 0.068671 0.068612
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1 0.081680 0.082105 0.071274 0.071854 0.072470 0.073113 0.073773
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2 0.075858 0.076636 0.065396 0.066119 0.066891 0.067709 0.068568
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3 0.088410 0.088369 0.079741 0.080197 0.080665 0.081133 0.081581
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4 0.087566 0.087768 0.078433 0.079026 0.079640 0.080262 0.080878
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5 0.086291 0.086762 0.076697 0.077431 0.078196 0.078981 0.079775
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6 0.083628 0.083348 0.077121 0.077466 0.077810 0.078139 0.078433
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7 0.083894 0.083777 0.077004 0.077460 0.077920 0.078370 0.078791
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8 0.084078 0.084137 0.076786 0.077358 0.077938 0.078514 0.079067
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9 0.084137 0.084387 0.076427 0.077117 0.077822 0.078529 0.079223
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10 0.076786 0.076427 0.071915 0.072200 0.072478 0.072735 0.072954
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11 0.077358 0.077117 0.072200 0.072576 0.072948 0.073302 0.073621
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12 0.077938 0.077822 0.072478 0.072948 0.073417 0.073871 0.074292
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13 0.078514 0.078529 0.072735 0.073302 0.073871 0.074428 0.074956
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14 0.079067 0.079223 0.072954 0.073621 0.074292 0.074956 0.075597
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</pre></div>
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</div>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>
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</pre></div>
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</div>
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</div>
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