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<title>Visually exploring local explanations to understand complex machine learning models</title>
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<section id="title-slide" data-background-image="img/penguins_bg.png" data-background-position="30% 45%" data-background-size="90%" class="center">
<h1 class="title">Visually exploring local explanations to understand complex machine learning models</h1>
<p class="author">Professor Di Cook <br> Monash University <br><br> <span class="citation" data-cites="visnut">@visnut</span><span class="citation" data-cites="aus.social">@aus.social</span></p>
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<h2>Outline</h2>
<ul>
<li>Example data: penguins</li>
<li>Tours: visualising high-dimensions with linear projections</li>
<li>XAI and local explanations</li>
<li>Demo</li>
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<section id="example-data-palmer-penguins" class="slide level2" data-background-image="https://allisonhorst.github.io/palmerpenguins/logo.png" data-background-size="100px" data-background-position="96% 1%">
<h2>Example data: Palmer penguins</h2>
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class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>species<\/th>\n <th>island<\/th>\n <th>bill_length_mm<\/th>\n <th>bill_depth_mm<\/th>\n <th>flipper_length_mm<\/th>\n <th>body_mass_g<\/th>\n <th>sex<\/th>\n <th>year<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":5,"columnDefs":[{"className":"dt-right","targets":[3,4,5,6,8]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[5,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>
</div>
</div>
<aside><div>
<p>See <a href="https://allisonhorst.github.io/palmerpenguins/">Allison Horst’s web site on the penguins data</a> for more details.</p>
</div></aside></section>
<section id="pre-process-data" class="slide level2">
<h2>Pre-process data</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1"></a>penguins <span class="ot"><-</span> penguins <span class="sc">%>%</span></span>
<span id="cb1-2"><a href="#cb1-2"></a> <span class="fu">na.omit</span>() <span class="co"># 11 observations out of 344 removed</span></span>
<span id="cb1-3"><a href="#cb1-3"></a><span class="co"># use only vars of interest, and standardise</span></span>
<span id="cb1-4"><a href="#cb1-4"></a><span class="co"># them for easier interpretation</span></span>
<span id="cb1-5"><a href="#cb1-5"></a>penguins_sub <span class="ot"><-</span> penguins[,<span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">3</span><span class="sc">:</span><span class="dv">6</span>)] <span class="sc">%>%</span> </span>
<span id="cb1-6"><a href="#cb1-6"></a> <span class="fu">mutate</span>(<span class="fu">across</span>(<span class="fu">where</span>(is.numeric), <span class="sc">~</span> <span class="fu">scale</span>(.)[,<span class="dv">1</span>])) <span class="sc">%>%</span></span>
<span id="cb1-7"><a href="#cb1-7"></a> <span class="fu">rename</span>(<span class="at">bl =</span> bill_length_mm,</span>
<span id="cb1-8"><a href="#cb1-8"></a> <span class="at">bd =</span> bill_depth_mm,</span>
<span id="cb1-9"><a href="#cb1-9"></a> <span class="at">fl =</span> flipper_length_mm,</span>
<span id="cb1-10"><a href="#cb1-10"></a> <span class="at">bm =</span> body_mass_g)</span>
<span id="cb1-11"><a href="#cb1-11"></a><span class="fu">summary</span>(penguins_sub)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>#> species bl bd fl
#> Adelie :146 Min. :-2.17 Min. :-2.06 Min. :-2.07
#> Chinstrap: 68 1st Qu.:-0.82 1st Qu.:-0.79 1st Qu.:-0.78
#> Gentoo :119 Median : 0.09 Median : 0.07 Median :-0.28
#> Mean : 0.00 Mean : 0.00 Mean : 0.00
#> 3rd Qu.: 0.84 3rd Qu.: 0.78 3rd Qu.: 0.86
#> Max. : 2.85 Max. : 2.20 Max. : 2.14
#> bm
#> Min. :-1.87
#> 1st Qu.:-0.82
#> Median :-0.20
#> Mean : 0.00
#> 3rd Qu.: 0.71
#> Max. : 2.60</code></pre>
</div>
</div>
</section>
<section id="examine-the-penguins-using-a-tour" class="slide level2">
<h2>Examine the penguins using a tour</h2>
<div class="cell" data-layout-align="center">
</div>
<div class="column" style="width:45%;">
<p><strong>Grand tour</strong>: randomly selecting target planes</p>
<p><img data-src="penguins_gt.gif" style="width:100.0%;height:100.0%"></p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<br> <br> <br> <br> <br>
<p style="color: #1B9E77">
Adelie
</p>
<p style="color: #D95F02">
Chinstrap
</p>
<p style="color: #7570B3">
Gentoo
</p>
</div>
</section>
<section id="examine-the-penguins-using-a-tour-1" class="slide level2">
<h2>Examine the penguins using a tour</h2>
<div class="column" style="width:45%;">
<p><strong>Grand tour</strong>: randomly selecting target planes</p>
<p><img data-src="img/penguins_gt.png" style="width:100.0%;height:100.0%"></p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<p><strong>Guided tour</strong>: target planes chosen to best separate classes</p>
<p><img data-src="penguins_pp.gif" style="width:100.0%;height:100.0%"></p>
</div>
</section>
<section id="tour-projections-are-biplots" class="slide level2">
<h2>Tour projections are biplots</h2>
<div class="column" style="width:45%;">
<p><img data-src="img/penguins_pp.png" style="width:100.0%;height:100.0%"></p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<p><code>bd</code> and <code>bm</code> distinguish <strong style="color: #7570B3"> Gentoo </strong></p>
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-5-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
</section>
<section id="tour-projections-are-biplots-1" class="slide level2">
<h2>Tour projections are biplots</h2>
<div class="column" style="width:45%;">
<p><img data-src="img/penguins_pp.png" style="width:100.0%;height:100.0%"></p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<p><code>bd</code> and <code>fl</code> also distinguish <strong style="color: #7570B3"> Gentoo </strong></p>
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-6-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
</section>
<section id="tour-projections-are-biplots-2" class="slide level2">
<h2>Tour projections are biplots</h2>
<div class="column" style="width:45%;">
<p><img data-src="img/penguins_pp.png" style="width:100.0%;height:100.0%"></p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<p><code>bd</code> and <code>bl</code> distinguish <strong style="color: #D95F02"> Chinstrap </strong> from <strong style="color: #1B9E77"> Adelie </strong></p>
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-7-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
</section>
<section id="fit-a-classification-model" class="slide level2">
<h2>Fit a classification model</h2>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1"></a><span class="fu">library</span>(randomForest)</span>
<span id="cb3-2"><a href="#cb3-2"></a><span class="fu">set.seed</span>(<span class="dv">2311</span>)</span>
<span id="cb3-3"><a href="#cb3-3"></a>penguins_rf_cl <span class="ot"><-</span> <span class="fu">randomForest</span>(species<span class="sc">~</span>., penguins_sub, </span>
<span id="cb3-4"><a href="#cb3-4"></a> <span class="at">ntree =</span> <span class="dv">1000</span>,</span>
<span id="cb3-5"><a href="#cb3-5"></a> <span class="at">importance =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p><br></p>
<div class="cell" data-layout-align="center">
<div class="cell-output cell-output-stdout">
<pre><code>#>
#> Call:
#> randomForest(formula = species ~ ., data = penguins_sub, ntree = 1000, importance = TRUE)
#> Type of random forest: classification
#> Number of trees: 1000
#> No. of variables tried at each split: 2
#>
#> OOB estimate of error rate: 2.4%
#> Confusion matrix:
#> Adelie Chinstrap Gentoo class.error
#> Adelie 143 3 0 0.0205
#> Chinstrap 4 64 0 0.0588
#> Gentoo 0 1 118 0.0084</code></pre>
</div>
</div>
</section>
<section id="variable-importance-globally" class="slide level2">
<h2>Variable importance (globally)</h2>
<div class="cell" data-layout-align="center">
<div class="cell-output cell-output-stdout">
<pre><code>#> Adelie Chinstrap Gentoo MeanDecreaseAccuracy MeanDecreaseGini
#> bl 0.454 0.38 0.098 0.31 88
#> bd 0.080 0.13 0.299 0.17 40
#> fl 0.128 0.12 0.336 0.20 67
#> bm 0.015 0.14 0.154 0.09 18</code></pre>
</div>
</div>
<div class="column" style="width:45%;">
<p>Globally, <code>bl</code>, <code>fl</code> are most important, and to a lesser extent, <code>bd</code> and even lesser extent <code>bm</code>. <text style="color:#aec7b2"> (Note: one needs to play with sign.) </text></p>
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1"></a>lin1 <span class="ot"><-</span> penguins_rf_cl<span class="sc">$</span>importance[,<span class="dv">4</span>]<span class="sc">/</span></span>
<span id="cb6-2"><a href="#cb6-2"></a> <span class="fu">sqrt</span>(<span class="fu">sum</span>(penguins_rf_cl<span class="sc">$</span>importance[,<span class="dv">4</span>]<span class="sc">^</span><span class="dv">2</span>))</span>
<span id="cb6-3"><a href="#cb6-3"></a><span class="co"># Flip sign of one</span></span>
<span id="cb6-4"><a href="#cb6-4"></a>lin1[<span class="dv">2</span>] <span class="ot"><-</span> <span class="sc">-</span>lin1[<span class="dv">2</span>]</span>
<span id="cb6-5"><a href="#cb6-5"></a>proj1 <span class="ot"><-</span> <span class="fu">as.matrix</span>(penguins_sub[,<span class="sc">-</span><span class="dv">1</span>])<span class="sc">%*%</span><span class="fu">as.matrix</span>(lin1)</span>
<span id="cb6-6"><a href="#cb6-6"></a>penguins_pred <span class="ot"><-</span> penguins_sub <span class="sc">%>%</span> </span>
<span id="cb6-7"><a href="#cb6-7"></a> <span class="fu">mutate</span>(<span class="at">proj1=</span>proj1)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-12-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
</section>
<section id="variable-importance-by-class" class="slide level2">
<h2>Variable importance (by class)</h2>
<div class="cell" data-layout-align="center">
<div class="cell-output cell-output-stdout">
<pre><code>#> Adelie Chinstrap Gentoo MeanDecreaseAccuracy MeanDecreaseGini
#> bl 0.454 0.38 0.098 0.31 88
#> bd 0.080 0.13 0.299 0.17 40
#> fl 0.128 0.12 0.336 0.20 67
#> bm 0.015 0.14 0.154 0.09 18</code></pre>
</div>
</div>
<div class="column" style="width:30%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-14-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
<div class="column" style="width:30%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-15-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
<div class="column" style="width:30%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-16-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
<p><text style="color:#aec7b2"> Note: one still needs to play with sign.</text></p>
</section>
<section id="radial-tours-bd-is-very-important" class="slide level2">
<h2>Radial tours: <code>bd</code> is very important</h2>
<div class="cell" data-layout-align="center">
</div>
<div class="column" style="width:45%;">
<p>A radial tour changes the contribution for one variable, reducing it to 0, and then back to original.</p>
<p>At right, cofficient for <code>bd</code> is being changed.</p>
<p>When it is 0, gap between <strong style="color: #7570B3"> Gentoo </strong> and others is smaller, implying that <code>bd</code> is very important.</p>
</div>
<div class="column" style="width:45%;">
<p><img data-src="penguins_rt_bd.gif" style="width:100.0%;height:100.0%"></p>
</div>
</section>
<section id="but-bl-is-less-important" class="slide level2">
<h2>but <code>bl</code> is less important</h2>
<div class="column" style="width:45%;">
<p>At right, the small contribution for <code>bl</code> is reduced to zero, which does not change the gap between <strong style="color: #7570B3"> Gentoo </strong> and others.</p>
<p>Thus <code>bl</code> can be removed from the projection, to make a simpler but equally effective combination of variables.</p>
</div>
<div class="column" style="width:45%;">
<p><img data-src="penguins_rt_bl.gif" style="width:100.0%;height:100.0%"></p>
</div>
</section>
<section id="view-of-the-model" class="slide level2">
<h2>View of the model</h2>
<div class="column" style="width:45%;">
<div class="cell" data-layout-align="center">
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1"></a><span class="fu">set.seed</span>(<span class="dv">1124</span>)</span>
<span id="cb8-2"><a href="#cb8-2"></a>penguins_grid <span class="ot"><-</span> <span class="fu">tibble</span>(<span class="at">bl=</span><span class="fu">runif</span>(<span class="dv">1000</span>, <span class="sc">-</span><span class="dv">3</span>, <span class="dv">3</span>),</span>
<span id="cb8-3"><a href="#cb8-3"></a> <span class="at">bd=</span><span class="fu">runif</span>(<span class="dv">1000</span>, <span class="sc">-</span><span class="dv">3</span>, <span class="dv">3</span>),</span>
<span id="cb8-4"><a href="#cb8-4"></a> <span class="at">fl=</span><span class="fu">runif</span>(<span class="dv">1000</span>, <span class="sc">-</span><span class="dv">3</span>, <span class="dv">3</span>),</span>
<span id="cb8-5"><a href="#cb8-5"></a> <span class="at">bm=</span><span class="fu">runif</span>(<span class="dv">1000</span>, <span class="sc">-</span><span class="dv">3</span>, <span class="dv">3</span>))</span>
<span id="cb8-6"><a href="#cb8-6"></a>penguins_grid <span class="ot"><-</span> penguins_grid <span class="sc">%>%</span></span>
<span id="cb8-7"><a href="#cb8-7"></a> <span class="fu">mutate</span>(<span class="at">pred =</span> <span class="fu">predict</span>(penguins_rf_cl, penguins_grid))</span>
<span id="cb8-8"><a href="#cb8-8"></a><span class="fu">load</span>(<span class="st">"data/penguins_pp.rda"</span>)</span>
<span id="cb8-9"><a href="#cb8-9"></a>proj <span class="ot"><-</span> <span class="fu">as.matrix</span>(pp<span class="sc">$</span>basis[[<span class="fu">dim</span>(pp)[<span class="dv">1</span>]]])</span>
<span id="cb8-10"><a href="#cb8-10"></a>penguins_grid <span class="ot"><-</span> penguins_grid <span class="sc">%>%</span></span>
<span id="cb8-11"><a href="#cb8-11"></a> <span class="fu">mutate</span>(<span class="at">pp1 =</span> <span class="fu">as.matrix</span>(penguins_grid[,<span class="dv">1</span><span class="sc">:</span><span class="dv">4</span>])<span class="sc">%*%</span>proj[,<span class="dv">1</span>],</span>
<span id="cb8-12"><a href="#cb8-12"></a> <span class="at">pp2 =</span> <span class="fu">as.matrix</span>(penguins_grid[,<span class="dv">1</span><span class="sc">:</span><span class="dv">4</span>])<span class="sc">%*%</span>proj[,<span class="dv">2</span>])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<div class="cell" data-layout-align="center">
</div>
<div class="cell" data-layout-align="center">
</div>
<p>Global importance cannot provide a single linear view revealing all aspects of the model.</p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<p><img data-src="img/penguins_model.png" style="width:100.0%;height:100.0%"></p>
</div>
</section>
<section id="local-explanations" class="slide level2">
<h2>Local explanations</h2>
<p>Explainable Artificial Intelligence (XAI) is an emerging field of research that provides methods for the interpreting of black box models<sup>1</sup>.</p>
<p>A common approach is to use <strong style="color:#aec7b2"> local explanations</strong>, which attempt to approximate linear variable importance in the neighbourhood each observation.</p>
<div class="column" style="width:40%;">
<p>Fitted model may be highly nonlinear. Overall linear projection will not accurately represent the fit in all subspaces.</p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:40%;">
<p><img data-src="img/penguins_pp_le.png" style="width:70.0%;height:70.0%"></p>
</div>
<aside><ol class="aside-footnotes"><li id="fn1" role="doc-endnote"><p><a href="https://ieeexplore.ieee.org/document/8466590">Adadi and Berrada 2018</a>; <a href="https://www.sciencedirect.com/science/article/abs/pii/S1566253519308103">Arrieta et al. 2020</a></p></li></ol></aside></section>
<section id="compute-shap-values" class="slide level2">
<h2>Compute SHAP values</h2>
<div class="column" style="width:80%;">
<div class="cell" data-layout-align="center">
</div>
<div class="cell" data-layout-align="center">
</div>
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div id="htmlwidget-624a5611a6c5714fbf00" style="width:100%;height:auto;" class="datatables html-widget"></div>
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class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>species<\/th>\n <th>pspecies<\/th>\n <th>bl<\/th>\n <th>bd<\/th>\n <th>fl<\/th>\n <th>bm<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":5,"columnDefs":[{"targets":3,"render":"function(data, type, row, meta) {\n return type !== 'display' ? data : DTWidget.formatRound(data, 3, 3, \",\", \".\", null);\n }"},{"targets":4,"render":"function(data, type, row, meta) {\n return type !== 'display' ? data : DTWidget.formatRound(data, 3, 3, \",\", \".\", null);\n }"},{"targets":5,"render":"function(data, type, row, meta) {\n return type !== 'display' ? data : DTWidget.formatRound(data, 3, 3, \",\", \".\", null);\n }"},{"targets":6,"render":"function(data, type, row, meta) {\n return type !== 'display' ? data : DTWidget.formatRound(data, 3, 3, \",\", \".\", null);\n 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</div>
</div>
<div class="cell" data-layout-align="center">
</div>
</div>
<div class="column" style="width:3%;">
</div>
<div class="column" style="width:15%;">
<p><br> Each observation has a variable importance, computed using the SHAP method.</p>
</div>
</section>
<section id="common-methods-for-local-explanations" class="slide level2">
<h2>Common methods for local explanations</h2>
<ul>
<li><strong style="color:#aec7b2"> SHAP </strong> is computed at each observation, by examining predictions while varying one variable and holding others fixed at mean, see <a href="https://christophm.github.io/interpretable-ml-book/shap.html">Molnar (2022) Interpretable Machine Learning</a>.</li>
<li><strong style="color:#aec7b2"> LIME </strong> examines predictions at each observation from randomly generated new observations in local neighbourhood, see <a href="https://numbat.space/post/lime/">Mason (2020)</a>.</li>
</ul>
</section>
<section id="comparing-local-explanations-of-all" class="slide level2">
<h2>Comparing local explanations of all</h2>
<div class="column" style="width:50%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-25-1.png" style="width:100.0%"></p>
</figure>
</div>
</div>
</div>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:40%;">
<p><br> Observations with different local explanations from the rest of their group are likely the misclassified cases.</p>
<p>And from the parallel coordinate plot can be seen which variables are most contributing to this.</p>
</div>
</section>
<section id="demo" class="slide level2">
<h2>Demo</h2>
<p><br> <br> <br> <br> Exploring the local explanations, with a radial tour, using cheem: <a href="https://ebsmonash.shinyapps.io/cheem_initial/">https://ebsmonash.shinyapps.io/cheem_initial/</a></p>
</section>
<section id="what-we-learn" class="slide level2">
<h2>What we learn</h2>
<center>
<img data-src="img/penguins_cheem1.png" style="width:70.0%">
</center>
<p>For this <strong style="color: #7570B3"> Gentoo </strong> penguin, mistaken to be a <strong style="color: #D95F02"> Chinstrap</strong>, the model used only a small component of <code>fl</code>, unlike the other Gentoo but more like the bulk of the Chinstrap penguins. The <code>fl</code> component is an important difference between this penguin and others in it’s species.</p>
</section>
<section id="what-we-learn-1" class="slide level2">
<h2>What we learn</h2>
<div class="column" style="width:45%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="slides_files/figure-revealjs/unnamed-chunk-26-1.png" style="width:80.0%"></p>
</figure>
</div>
</div>
</div>
<p>With <code>fl</code> it looks more like a Chinstrap.</p>
</div>
<div class="column" style="width:5%;">
</div>
<div class="column" style="width:45%;">
<div class="cell" data-layout-align="center">
<div class="cell-output-display">
<div class="quarto-figure quarto-figure-center">
<figure>
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<p>With only <code>bl</code> and <code>bd</code> it looks like it’s own species.</p>
</div>
</section>
<section id="summary" class="slide level2">
<h2>Summary</h2>
<p><br><br></p>
<ul>
<li>Local explanations tell us how a prediction is constructed, for any observation.</li>
<li>User-controlled, interactive radial tours are useful to check the local explanations, and better understand a model fit in local neighbourhoods.</li>
</ul>
</section>
<section id="further-reading" class="slide level2">
<h2>Further reading</h2>
<p>This work is based on Nick Spyrison’s PhD research, developed after discussions with Przemyslaw Biecek.</p>
<ul>
<li><a href="https://arxiv.org/abs/2205.05359">Spyrison, Cook, Biecek (2022)</a> Exploring Local Explanations of Nonlinear Models Using Animated Linear Projections</li>
<li><a href="https://nspyrison.github.io/cheem/">R package: cheem</a> and <a href="https://ebsmonash.shinyapps.io/cheem_initial/">shiny app for experimenting</a>.</li>
<li><a href="https://onlinelibrary.wiley.com/doi/10.1002/sam.11271">Wickham, Cook, Hofmann (2015)</a> Visualizing statistical models: Removing the blindfold.</li>
</ul>
</section>
<section id="acknowledgements" class="slide level2">
<h2>Acknowledgements</h2>
<p>Slides produced using <a href="https://quarto.org">quarto</a>.</p>
<p>Slides available from <a href="https://github.com/dicook/Stellenbosch_2022" class="uri">https://github.com/dicook/Stellenbosch_2022</a>.</p>
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