def load_grid_tiny():
    """ 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
        List of 10 parameter configurations that are likely to perform 
        reasonably well.

    """
    pg = [{'p': [2.0], 'kappa': [5.0], 'lmd': [pow(2, -16)], 'weights': [
        'unit']}, {'p': [2.0], 'kappa': [5.0], 'lmd': [pow(2, -18)],
        'weights': ['unit']}, {'p': [2.0], 'kappa': [0.5], 'lmd': [pow(2, -
        18)], 'weights': ['unit']}, {'p': [2.0], 'kappa': [5.0], 'lmd': [
        pow(2, -18)], 'weights': ['group']}, {'p': [2.0], 'kappa': [-0.9],
        'lmd': [pow(2, -18)], 'weights': ['unit']}, {'p': [2.0], 'kappa': [
        5.0], 'lmd': [pow(2, -14)], 'weights': ['unit']}, {'p': [2.0],
        'kappa': [0.5], 'lmd': [pow(2, -18)], 'weights': ['group']}, {'p':
        [1.5], 'kappa': [-0.9], 'lmd': [pow(2, -18)], 'weights': ['unit']},
        {'p': [2.0], 'kappa': [0.5], 'lmd': [pow(2, -16)], 'weights': [
        'unit']}, {'p': [2.0], 'kappa': [0.5], 'lmd': [pow(2, -16)],
        'weights': ['group']}]
    return pg
