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diff --git a/dev/accessor_functions/index.html b/dev/accessor_functions/index.html
diff --git a/dev/algorithm_traits/index.html b/dev/algorithm_traits/index.html
diff --git a/dev/anatomy_of_an_implementation/index.html b/dev/anatomy_of_an_implementation/index.html
@@ -46,12 +46,12 @@
 X = (; a, b, c) |&gt; Tables.rowtable
 y = 2a - b + 3c + 0.05*rand(n)</code></pre><p>Instantiate an algorithm with relevant hyperparameters (which is all the object stores):</p><pre><code class="language-julia hljs">algorithm = MyRidge(lambda=0.5)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">Main.MyRidge(0.5)</code></pre><p>Train the algorithm (the <code>0</code> means do so silently):</p><pre><code class="language-julia hljs">import LearnAPI: fit, predict, feature_importances
 
-fitted_params, state, fit_report = fit(algorithm, 0, X[train], y[train])</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">((coefficients = [2.115542219876959, 0.18376643926262562, 2.13381070722609],), nothing, (feature_importances = [:c =&gt; 2.13381070722609, :a =&gt; 2.115542219876959, :b =&gt; 0.18376643926262562],))</code></pre><p>Inspect the learned parameters and report:</p><pre><code class="language-julia hljs">@info &quot;training outcomes&quot; fitted_params fit_report</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">┌ Info: training outcomes
-│   fitted_params = (coefficients = [2.115542219876959, 0.18376643926262562, 2.13381070722609],)
-└   fit_report = (feature_importances = [:c =&gt; 2.13381070722609, :a =&gt; 2.115542219876959, :b =&gt; 0.18376643926262562],)</code></pre><p>Inspect feature importances:</p><pre><code class="language-julia hljs">feature_importances(algorithm, fitted_params, fit_report)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">3-element Vector{Pair{Symbol, Float64}}:
- :c =&gt; 2.13381070722609
- :a =&gt; 2.115542219876959
- :b =&gt; 0.18376643926262562</code></pre><p>Make a prediction using new data:</p><pre><code class="language-julia hljs">yhat, predict_report = predict(algorithm, LearnAPI.LiteralTarget(), fitted_params, X[test])</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([2.5959308560640078, 1.425858419169964, 0.38941751351521436, 3.7513504197315113], nothing)</code></pre><p>Compare predictions with ground truth</p><pre><code class="language-julia hljs">deviations = yhat - y[test]
+fitted_params, state, fit_report = fit(algorithm, 0, X[train], y[train])</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">((coefficients = [1.5446141519448298, 0.5373430048970873, 1.604168534610231],), nothing, (feature_importances = [:c =&gt; 1.604168534610231, :a =&gt; 1.5446141519448298, :b =&gt; 0.5373430048970873],))</code></pre><p>Inspect the learned parameters and report:</p><pre><code class="language-julia hljs">@info &quot;training outcomes&quot; fitted_params fit_report</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">┌ Info: training outcomes
+│   fitted_params = (coefficients = [1.5446141519448298, 0.5373430048970873, 1.604168534610231],)
+└   fit_report = (feature_importances = [:c =&gt; 1.604168534610231, :a =&gt; 1.5446141519448298, :b =&gt; 0.5373430048970873],)</code></pre><p>Inspect feature importances:</p><pre><code class="language-julia hljs">feature_importances(algorithm, fitted_params, fit_report)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">3-element Vector{Pair{Symbol, Float64}}:
+ :c =&gt; 1.604168534610231
+ :a =&gt; 1.5446141519448298
+ :b =&gt; 0.5373430048970873</code></pre><p>Make a prediction using new data:</p><pre><code class="language-julia hljs">yhat, predict_report = predict(algorithm, LearnAPI.LiteralTarget(), fitted_params, X[test])</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">([1.8434681263969486, 1.9144320174595624, 0.8289219470454475, 1.8206269299634923], nothing)</code></pre><p>Compare predictions with ground truth</p><pre><code class="language-julia hljs">deviations = yhat - y[test]
 loss = deviations .^2 |&gt; sum
 @info &quot;Sum of squares loss&quot; loss</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">┌ Info: Sum of squares loss
-└   loss = 1.3038472022774477</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../goals_and_approach/">« Goals and Approach</a><a class="docs-footer-nextpage" href="../reference/">Reference »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Wednesday 11 October 2023 03:52">Wednesday 11 October 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+└   loss = 1.675661967867687</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../goals_and_approach/">« Goals and Approach</a><a class="docs-footer-nextpage" href="../reference/">Reference »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 0.27.25 on <span class="colophon-date" title="Thursday 26 October 2023 20:59">Thursday 26 October 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
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