def _clean_nans(scores):
    # XXX where should this function be called? fit? scoring functions
    # themselves?
    scores = as_float_array(scores, copy=True)
    scores[np.isnan(scores)] = np.finfo(scores.dtype).min
    return scores


######################################################################
# Scoring functions


# The following function is a rewriting of scipy.stats.f_oneway
# Contrary to the scipy.stats.f_oneway implementation it does not
# copy the data while keeping the inputs unchanged.
Clear _seen property and set current user as seen
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/feature_selection/univariate_selection.py/_clean_nans--crossover with--dataset/ETHPy150Open frappe/frappe/frappe/model/document.py/Document.reset_seen