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@@ -527,8 +527,6 @@ of your model complexity (the degree of the polynomial) and the number
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of data points, and possibly also your training and test data using the <b>bootstrap</b> resampling method.
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You can follow the code example in the jupyter-book at <a href="https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/chapter3.html#the-bias-variance-tradeoff" target="_blank"><tt>https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/chapter3.html#the-bias-variance-tradeoff</tt></a>.
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</p>
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<p>Note also that when you calculate the bias, in all applications you don't know the function values \( f_i \). You would hence replace them with the actual data points \( y_i \).</p>
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<h3 id="part-d-cross-validation-as-resampling-techniques-adding-more-complexity">Part d): Cross-validation as resampling techniques, adding more complexity </h3>
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<p>The aim here is to write your own code for another widely popular
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