def get_stats_result(self, request):
        """Return the StatsResult object for this statistic"""
        stats_datasets = StatsMakerDataverses(**request.GET.dict())

        pub_state = self.get_pub_state(request)

        if pub_state == self.PUB_STATE_ALL:
            stats_result = stats_datasets.get_dataverse_counts_by_month()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_counts_by_month_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_counts_by_month_published()

        return stats_result
def compute_svm_cv(K, y, C=100.0, n_folds=5,
                   scoring=balanced_accuracy_scoring):
    """Compute cross-validated score of SVM with given precomputed kernel.
    """
    cv = StratifiedKFold(y, n_folds=n_folds)
    clf = SVC(C=C, kernel='precomputed', class_weight='auto')
    scores = cross_val_score(clf, K, y,
                             scoring=scoring, cv=cv)
    return scores.mean()