EASY: clean up meta example filenames

[karlnapf]

folders:
gaussian_processes -> gaussian_process
multiclass_classifier -> multiclass
binary_classifier -> binary

no folder names inside the program listing names, e.g.
gaussian_process_classifier -> classifier
multiclass_linearmachine -> linear
sparse_gaussian_process_regression -> sparse_regression
multiclass_logisticregression -> logistic_regression

no abbreviations
svm -> support_vector_machine
knn -> k_nearest_neighbors

etc.

Make sure to change the cookbook filenames in doc/cookbook as well (try your changes with make cookbook)

Good way to learn about the examples in Shogun while cleaning up a bit

[dgkim5360]

Hello, newbie here. May I work on this one? I managed to compile and install it on my Ubuntu machine, and it looks appropriate for me to do the first steps.

Thanks for the beginner-friendly issues 👍

[karlnapf]

sure go for it :)

[dgkim5360]

@karlnapf while working on the cookbook, I found some minor typos, e.g.,
in /doc/cookbook/source/examples/multiclass/k_nearest_neighbours.rst

diff --git a/doc/cookbook/source/examples/multiclass/k_nearest_neighbours.rst b/doc/cookbook/source/examples/multiclass/k_nearest_neighbours.rst
index 58d6c6f..b0888ce 100644
--- a/doc/cookbook/source/examples/multiclass/k_nearest_neighbours.rst
+++ b/doc/cookbook/source/examples/multiclass/k_nearest_neighbours.rst
@@ -8,7 +8,7 @@ For :math:`k=1`, the label for a test point :math:`x^*` is predicted to be the s
 
 .. math::
 
-   k=\argmin_j d(x^*, x_j).  
+   k=\arg\min_j d(x^*, x_j).  
    
 See Chapter 14 in :cite:`barber2012bayesian` for a detailed introduction.

Should I include such corrections, or just leave them untouched and commit for the original task?

[karlnapf]

Argmin should be defined. Check the cookbook readme it tell you where to put custom latex

[karlnapf]

If you find typos, make a separate pr

[shivampkumar]

Just starting out with Shogun. I will go with this one first...Is that cool? Or has it been handled?

[karlnapf]

Closed via #4055