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cleaning up

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Morten Hjorth-Jensen
2021-09-10 10:00:31 +02:00
parent f26299b098
commit e6ba08bee0
9 changed files with 38 additions and 21 deletions
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@@ -263,7 +263,7 @@ $$
<p>
Your code has to include a scaling of the data (for example by
subtracting the mean value), and
a split of the data in training and test data. For this part you can
a split of the data in training and test data. For this exercise you can
either write your own code or use for example the function for
splitting training data provided by the library <b>Scikit-Learn</b> (make
sure you have installed it). This function is called
@@ -382,7 +382,7 @@ one provided by <b>Scikit-Learn</b>.
Write your own code for the Ridge method, either using matrix
inversion or the singular value decomposition as done in the previous
exercise. Perform the same bootstrap analysis as in the
Exercise 2 (for the same polynomials) and the cross-validation part in part c) but now for different values of \( \lambda \). Compare and
Exercise 2 (for the same polynomials) and the cross-validation in exercise 3 but now for different values of \( \lambda \). Compare and
analyze your results with those obtained in exercises 1-3. Study the
dependence on \( \lambda \).
@@ -405,11 +405,14 @@ model fits the data best. Perform here as well an analysis of the bias-variance
<p>
With our codes functioning and having been tested properly on a
simpler function we are now ready to look at real data. We will
essentially repeat in part g) what was done in parts a-e). However, we
essentially repeat in this exercise what was done in exercises 1-5. However, we
need first to download the data and prepare properly the inputs to our
codes. We are going to download digital terrain data from the website
<a href="https://earthexplorer.usgs.gov/" target="_blank"><tt>https://earthexplorer.usgs.gov/</tt></a>,
<p>
Or, if you prefer, we have placed selected datafiles at <a href="https://github.com/CompPhysics/MachineLearning/tree/master/doc/Projects/2021/Project1/DataFiles" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/tree/master/doc/Projects/2021/Project1/DataFiles</tt></a>
<p>
In order to obtain data for a specific region, you need to register as
a user (free) at this website and then decide upon which area you want