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cm016.html
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<h1 class="title toc-ignore">Statistical learning: resampling and decision trees</h1>
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<div id="cm016---november-16-2016" class="section level1">
<h1>cm016 - November 16, 2016</h1>
<div id="overview" class="section level2">
<h2>Overview</h2>
<ul>
<li>Define resampling methods</li>
<li>Review the validation set approach using linear regression</li>
<li>Explain leave-one-out cross-validation</li>
<li>Explain <span class="math inline">\(k\)</span>-fold cross-validation</li>
<li>Demonstrate how to conduct cross-validation on generalized linear models</li>
<li>Define a decision tree</li>
<li>Demonstrate how to estimate a decision tree</li>
<li>Define and estimate a random forest</li>
<li>Introduce the <code>caret</code> package for statistical learning in R</li>
</ul>
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<div id="slides-and-links" class="section level2">
<h2>Slides and links</h2>
<ul>
<li><a href="stat_learning02.html">Notes from class</a></li>
<li><p><a href="extras/cm016_slides.html">Slides</a></p></li>
<li><p><a href="https://topepo.github.io/caret/">The <code>caret</code> Package</a> - introductory book for the <code>caret</code> package. Tells you what models you can implement and all the nitty-gritty details to customize <code>train</code> for different cross-validation methods.</p></li>
</ul>
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<h2>To do for Monday</h2>
<ul>
<li><a href="hw08-statistical_learning.html">Start homework 8</a></li>
<li>Final projects people! Get started on them.
<ul>
<li><a href="https://github.com/uc-cfss/fp-template">Starter repo for the project</a> - check this demo out of an R Markdown website. This is what you will start with in your final project repo.</li>
<li><a href="https://uc-cfss.github.io/fp-template/">Rendered version of the template</a></li>
<li><a href="https://classroom.github.com/assignment-invitations/9ebfcbb562ac99780788dd2ca9101986">Clone your final project repo</a></li>
</ul></li>
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<p>This work is licensed under the <a href="http://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC 4.0 Creative Commons License</a>.</p>
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