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Morten Hjorth-Jensen
2023-09-11 06:41:34 +02:00
parent b7e90afa3a
commit 125231ac1a
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@@ -278,6 +278,28 @@ const thebe_selector_output = ".output, .cell_output"
Week 36: Statistical interpretation of Linear Regression and Resampling techniques
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</li>
<li class="toctree-l1">
<a class="reference internal" href="exercisesweek37.html">
Exercises week 37
</a>
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<li class="toctree-l1">
<a class="reference internal" href="week37.html">
Week 37: Statitsitcal interpretations and Resampling Methods
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</ul>
<p aria-level="2" class="caption" role="heading">
<span class="caption-text">
Projects
</span>
</p>
<ul class="nav bd-sidenav">
<li class="toctree-l1">
<a class="reference internal" href="project1.html">
Project 1 on Machine Learning, deadline October 9 (midnight), 2023
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</li>
</ul>
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@@ -797,10 +819,10 @@ number <span class="math notranslate nohighlight">\(i\)</span> is left out. Usin
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Runtime: 0.0907788 sec
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Runtime: 0.101292 sec
Jackknife Statistics :
original bias std. error
100.022 100.012 0.148734
99.9618 99.9518 0.148771
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@@ -1019,7 +1041,7 @@ theorem.</p>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Bootstrap Statistics :
original bias std. error
99.7522 14.9594 99.7525 0.149991
99.9169 14.873 99.9169 0.147934
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@@ -1273,9 +1295,7 @@ Error: 0.021592704588021178
Bias^2: 0.010516485576646504
Var: 0.01107621901137467
0.021592704588021178 &gt;= 0.010516485576646504 + 0.01107621901137467 = 0.021592704588021174
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Polynomial degree: 11
Polynomial degree: 11
Error: 0.07160048164232538
Bias^2: 0.014436800088896381
Var: 0.05716368155342902
@@ -1285,7 +1305,9 @@ Error: 0.11547777218876518
Bias^2: 0.016285782696017142
Var: 0.09919198949274803
0.11547777218876518 &gt;= 0.016285782696017142 + 0.09919198949274803 = 0.11547777218876518
Polynomial degree: 13
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Polynomial degree: 13
Error: 0.2284246870217162
Bias^2: 0.01975416527168255
Var: 0.20867052175003364
@@ -1545,12 +1567,12 @@ Mean squared error on test data: 0.17446471
Degree of polynomial: 13
Mean squared error on training data: 0.00759119
Mean squared error on test data: 1.08131003
Degree of polynomial: 14
Mean squared error on training data: 0.00472199
Mean squared error on test data: 0.81333804
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Degree of polynomial: 15
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Degree of polynomial: 14
Mean squared error on training data: 0.00472199
Mean squared error on test data: 0.81333804
Degree of polynomial: 15
Mean squared error on training data: 0.00410478
Mean squared error on test data: 92.09172409
Degree of polynomial: 16
@@ -1588,12 +1610,12 @@ Mean squared error on test data: 128664.31650694
Degree of polynomial: 26
Mean squared error on training data: 0.00076905
Mean squared error on test data: 19003.94822514
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Degree of polynomial: 27
Degree of polynomial: 27
Mean squared error on training data: 0.00068946
Mean squared error on test data: 2379.66219404
Degree of polynomial: 28
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Degree of polynomial: 28
Mean squared error on training data: 0.00062595
Mean squared error on test data: 4082.19983530
Degree of polynomial: 29
@@ -1601,9 +1623,9 @@ Mean squared error on training data: 0.00060705
Mean squared error on test data: 3250.17647619
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/626635268.py:73: RuntimeWarning: divide by zero encountered in log10
<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/626635268.py:73: RuntimeWarning: divide by zero encountered in log10
plt.plot(polynomial, np.log10(trainingerror), label=&#39;Training Error&#39;)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/626635268.py:74: RuntimeWarning: divide by zero encountered in log10
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/626635268.py:74: RuntimeWarning: divide by zero encountered in log10
plt.plot(polynomial, np.log10(testerror), label=&#39;Test Error&#39;)
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@@ -1837,7 +1859,7 @@ cross-validation (LOOCV).</p>
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3817475779.py:63: RuntimeWarning: divide by zero encountered in log10
plt.plot(polynomial, np.log10(estimated_mse_sklearn), label=&#39;Test Error&#39;)
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@@ -2726,9 +2748,9 @@ linear system as an equation would reduce this down to
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/4162706317.py:6: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
cb = fig.colorbar(im)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/4162706317.py:7: UserWarning: FixedFormatter should only be used together with FixedLocator
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/4162706317.py:7: UserWarning: FixedFormatter should only be used together with FixedLocator
cb.ax.set_yticklabels(cb.ax.get_yticklabels(), fontsize=18)
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@@ -2872,9 +2894,9 @@ with the form utilized in linear regression, viz.</p>
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/3777801602.py:6: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3777801602.py:6: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
cb = fig.colorbar(im)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/3777801602.py:7: UserWarning: FixedFormatter should only be used together with FixedLocator
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3777801602.py:7: UserWarning: FixedFormatter should only be used together with FixedLocator
cb.ax.set_yticklabels(cb.ax.get_yticklabels(), fontsize=18)
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@@ -2914,9 +2936,9 @@ cost function is given by</p>
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/438060758.py:9: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
cb = fig.colorbar(im)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/438060758.py:10: UserWarning: FixedFormatter should only be used together with FixedLocator
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/438060758.py:10: UserWarning: FixedFormatter should only be used together with FixedLocator
cb.ax.set_yticklabels(cb.ax.get_yticklabels(), fontsize=18)
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@@ -2951,9 +2973,9 @@ cost function is given by</p>
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/3544313922.py:8: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3544313922.py:8: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
cb = fig.colorbar(im)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/3544313922.py:9: UserWarning: FixedFormatter should only be used together with FixedLocator
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3544313922.py:9: UserWarning: FixedFormatter should only be used together with FixedLocator
cb.ax.set_yticklabels(cb.ax.get_yticklabels(), fontsize=18)
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model = cd_fast.enet_coordinate_descent(
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@@ -3189,9 +3211,9 @@ which polynomial fits the data best.</p>
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ax = fig.gca(projection=&#39;3d&#39;)
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_16213/3980313467.py:37: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_7650/3980313467.py:37: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.
fig.colorbar(surf, shrink=0.5, aspect=5)
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