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Re-render sample post #729

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53 changes: 23 additions & 30 deletions content/blog/rsample-1-3-0/index.md
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Expand Up @@ -178,20 +178,20 @@ Now we have everything we need to calculate the confidence intervals, stashed in

<pre class='chroma'><code class='language-r' data-lang='r'><span><span class='nv'>item_ci</span> <span class='o'>&lt;-</span> <span class='nf'><a href='https://rsample.tidymodels.org/reference/int_pctl.html'>int_pctl</a></span><span class='o'>(</span><span class='nv'>item_stats</span>, statistics <span class='o'>=</span> <span class='nv'>stats</span>, alpha <span class='o'>=</span> <span class='m'>0.1</span><span class='o'>)</span></span>
<span><span class='nv'>item_ci</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># A tibble: 27 × 6</span></span></span>
<span><span class='c'>#&gt; term .lower .estimate .upper .alpha .method </span></span>
<span><span class='c'>#&gt; <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> </span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 1</span> item_01 1.04 1.07 1.10 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 2</span> item_02 0.999 1.02 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 3</span> item_03 0.974 1.01 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 4</span> item_04 0.991 1.01 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 5</span> item_05 0.984 1.00 1.02 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 6</span> item_06 0.996 1.02 1.05 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 7</span> item_07 0.992 1.02 1.04 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 8</span> item_08 0.993 1.01 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 9</span> item_09 0.996 1.01 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'>10</span> item_10 1.04 1.06 1.09 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># ℹ 17 more rows</span></span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># A tibble: 54 × 7</span></span></span>
<span><span class='c'>#&gt; term .weekend .lower .estimate .upper .alpha .method </span></span>
<span><span class='c'>#&gt; <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;dbl&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> </span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 1</span> item_01 weekday 1.05 1.07 1.09 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 2</span> item_01 weekend 1.04 1.07 1.10 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 3</span> item_02 weekday 1.00 1.02 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 4</span> item_02 weekend 0.996 1.01 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 5</span> item_03 weekday 1.01 1.02 1.04 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 6</span> item_03 weekend 0.970 0.990 1.01 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 7</span> item_04 weekday 0.989 1.00 1.02 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 8</span> item_04 weekend 0.998 1.02 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 9</span> item_05 weekday 0.987 1.00 1.02 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'>10</span> item_05 weekend 0.982 1.00 1.03 0.1 percentile</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># ℹ 44 more rows</span></span></span>
<span></span></code></pre>

</div>
Expand All @@ -209,21 +209,11 @@ It was possible, however, to create implicit LOO samples by using [`vfold_cv()`]
<div class="highlight">

<pre class='chroma'><code class='language-r' data-lang='r'><span><span class='nf'><a href='https://rsample.tidymodels.org/reference/vfold_cv.html'>vfold_cv</a></span><span class='o'>(</span><span class='nv'>mtcars</span>, v <span class='o'>=</span> <span class='nf'><a href='https://rdrr.io/r/base/nrow.html'>nrow</a></span><span class='o'>(</span><span class='nv'>mtcars</span><span class='o'>)</span><span class='o'>)</span></span>
<span><span class='c'>#&gt; # 32-fold cross-validation </span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># A tibble: 32 × 2</span></span></span>
<span><span class='c'>#&gt; splits id </span></span>
<span><span class='c'>#&gt; <span style='color: #555555; font-style: italic;'>&lt;list&gt;</span> <span style='color: #555555; font-style: italic;'>&lt;chr&gt;</span> </span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 1</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold01</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 2</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold02</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 3</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold03</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 4</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold04</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 5</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold05</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 6</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold06</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 7</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold07</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 8</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold08</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'> 9</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold09</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'>10</span> <span style='color: #555555;'>&lt;split [31/1]&gt;</span> Fold10</span></span>
<span><span class='c'>#&gt; <span style='color: #555555;'># ℹ 22 more rows</span></span></span>
<span><span class='c'>#&gt; <span style='color: #BBBB00; font-weight: bold;'>Error</span><span style='font-weight: bold;'> in `vfold_cv()`:</span></span></span>
<span><span class='c'>#&gt; <span style='color: #BBBB00;'>!</span> Leave-one-out cross-validation is not supported by this function.</span></span>
<span><span class='c'>#&gt; <span style='color: #BB0000;'>✖</span> You set `v` to `nrow(data)`, which would result in a leave-one-out</span></span>
<span><span class='c'>#&gt; cross-validation.</span></span>
<span><span class='c'>#&gt; <span style='color: #00BBBB;'>ℹ</span> Use `loo_cv()` in this case.</span></span>
<span></span></code></pre>

</div>
Expand All @@ -238,7 +228,10 @@ For some error messages, the additional functionality in cli makes it easy to im

<pre class='chroma'><code class='language-r' data-lang='r'><span><span class='nf'><a href='https://rsample.tidymodels.org/reference/permutations.html'>permutations</a></span><span class='o'>(</span><span class='nv'>mtcars</span>, <span class='nf'><a href='https://tidyselect.r-lib.org/reference/everything.html'>everything</a></span><span class='o'>(</span><span class='o'>)</span><span class='o'>)</span></span>
<span><span class='c'>#&gt; <span style='color: #BBBB00; font-weight: bold;'>Error</span><span style='font-weight: bold;'> in `permutations()`:</span></span></span>
<span><span class='c'>#&gt; <span style='color: #BBBB00;'>!</span> You have selected all columns to permute. This effectively reorders the rows in the original data without changing the data structure. Please select fewer columns to permute.</span></span>
<span><span class='c'>#&gt; <span style='color: #BBBB00;'>!</span> You have selected all columns to permute.</span></span>
<span><span class='c'>#&gt; <span style='color: #00BBBB;'>ℹ</span> This effectively reorders the rows in the original data without changing the</span></span>
<span><span class='c'>#&gt; data structure.</span></span>
<span><span class='c'>#&gt; → Please select fewer columns to permute.</span></span>
<span></span></code></pre>

</div>
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