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articles/AMR_with_tidymodels.html
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@ -142,7 +142,7 @@ package.</p>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">filter()</span> masks <span style="color: #0000BB;">stats</span>::filter()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">lag()</span> masks <span style="color: #0000BB;">stats</span>::lag()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">recipes</span>::<span style="color: #00BB00;">step()</span> masks <span style="color: #0000BB;">stats</span>::step()</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Use <span style="color: #00BB00;">tidymodels_prefer()</span> to resolve common conflicts.</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Dig deeper into tidy modeling with R at <span style="color: #00BB00;">https://www.tmwr.org</span></span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># For AMR data analysis</span></span>
<span></span>
<span><span class="co"># Load the example_isolates dataset</span></span>