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+
+.. py:function:: load_grid_tiny()
+   :noindex:
+   :module: gensvm.gridsearch
+
+   Load a tiny parameter grid for the GenSVM grid search
+   
+   This function returns a parameter grid to use in the GenSVM grid search.
+   This grid was obtained by analyzing the experiments done for the GenSVM
+   paper and selecting the configurations that achieve accuracy within the
+   95th percentile on over 90% of the datasets. It is a good start for a
+   parameter search with a reasonably high chance of achieving good
+   performance on most datasets.
+   
+   Note that this grid is only tested to work well in combination with the
+   linear kernel.
+   
+   :returns: **pg** -- List of 10 parameter configurations that are likely to perform
+             reasonably well.
+   :rtype: list
+   
+
+.. py:function:: load_grid_small()
+   :noindex:
+   :module: gensvm.gridsearch
+
+   Load a small parameter grid for GenSVM
+   
+   This function loads a default parameter grid to use for the #' GenSVM
+   gridsearch. It contains all possible combinations of the following #'
+   parameter sets::
+   
+       pg = {
+           'p': [1.0, 1.5, 2.0],
+           'lmd': [1e-8, 1e-6, 1e-4, 1e-2, 1],
+           'kappa': [-0.9, 0.5, 5.0],
+           'weights': ['unit', 'group'],
+       }
+   
+   :returns: **pg** -- Mapping from parameters to lists of values for those parameters. To be
+             used as input for the :class:`.GenSVMGridSearchCV` class.
+   :rtype: dict
+   
+
+.. py:function:: load_grid_full()
+   :noindex:
+   :module: gensvm.gridsearch
+
+   Load the full parameter grid for GenSVM
+   
+   This is the parameter grid used in the GenSVM paper to run the grid search
+   experiments. It uses a large grid for the ``lmd`` regularization parameter
+   and converges with a stopping criterion of ``1e-8``. This is a relatively
+   small stopping criterion and in practice good classification results can be
+   obtained by using a larger stopping criterion.
+   
+   The function returns the following grid::
+   
+       pg = {
+               'lmd': [pow(2, x) for x in range(-18, 19, 2)],
+               'kappa': [-0.9, 0.5, 5.0],
+               'p': [1.0, 1.5, 2.0],
+               'weights': ['unit', 'group'],
+               'epsilon': [1e-8],
+               'kernel': ['linear']
+            }
+   
+   :returns: **pg** -- Mapping from parameters to lists of values for those parameters. To be
+             used as input for the :class:`.GenSVMGridSearchCV` class.
+   :rtype: dict
+