updating book

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Morten Hjorth-Jensen
2023-09-18 12:44:58 +02:00
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<head>
<meta charset="utf-8" />
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<title>Data Analysis and Machine Learning: Logistic Regression and Optimization &#8212; Applied Data Analysis and Machine Learning</title>
<title>Week38: Logistic Regression and Optimization &#8212; Applied Data Analysis and Machine Learning</title>
<link href="_static/css/theme.css" rel="stylesheet">
<link href="_static/css/index.ff1ffe594081f20da1ef19478df9384b.css" rel="stylesheet">
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</li>
<li class="toctree-l1">
<a class="reference internal" href="week37.html">
Week 37: Statitsitcal interpretations and Resampling Methods
Week 37: Statistical interpretations and Resampling Methods
</a>
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Data Analysis and Machine Learning: Logistic Regression and Optimization
Week38: Logistic Regression and Optimization
</a>
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</ul>
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<h1>Data Analysis and Machine Learning: Logistic Regression and Optimization</h1>
<h1>Week38: Logistic Regression and Optimization</h1>
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<h1>Data Analysis and Machine Learning: Logistic Regression and Optimization<a class="headerlink" href="#data-analysis-and-machine-learning-logistic-regression-and-optimization" title="Permalink to this headline"></a></h1>
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<h1>Week38: Logistic Regression and Optimization<a class="headerlink" href="#week38-logistic-regression-and-optimization" title="Permalink to this headline"></a></h1>
<p><strong>Morten Hjorth-Jensen</strong>, Department of Physics and Center for Computing in Science Education, University of Oslo and Department of Physics and Astronomy and Facility for Rare Isotope Beams, Michigan State University</p>
<p>Date: <strong>September 18-22</strong></p>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>RandomizedSearchCV(estimator=Ridge(), n_iter=100,
param_distributions={&#39;alpha&#39;: &lt;scipy.stats._distn_infrastructure.rv_frozen object at 0x130057e80&gt;})
param_distributions={&#39;alpha&#39;: &lt;scipy.stats._distn_infrastructure.rv_frozen object at 0x128a2b580&gt;})
Best estimated lambda-value: 0.9849967686928113
MSE score: 1.0853136633465326
R2 score: -0.0002382102844775691