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@@ -320,8 +320,6 @@ 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 _bootstrap_ resampling method.
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You can follow the code example in the jupyter-book at URL:"https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/chapter3.html#the-bias-variance-tradeoff".
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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 $y_i$.
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=== Part d): Cross-validation as resampling techniques, adding more complexity ===
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