def load(self, filename, create_if_missing=True):
        filename = Path(filename)
        if not filename.exists() and create_if_missing:
            self.load_pip_requirements()
            with filename.open("w") as f:
                f.write(yaml.dump(self.serialized, default_flow_style=False,
                                  encoding=None))
            self.filename = filename
            return self.save(filename)
        with filename.open() as f:
            for group, requirements in yaml.load(f.read()).items():
                for requirement in requirements:
                    self[group].add(Requirement.coerce(requirement))
        self.filename = filename
def balanced_accuracy_scoring(clf, X, y):
    """Scoring function that computes the balanced accuracy to be used
    internally in the cross-validation procedure.
    """
    y_pred = clf.predict(X)
    conf_mat = confusion_matrix(y, y_pred)
    bal_acc = 0.
    for i in range(len(conf_mat)):
        bal_acc += (float(conf_mat[i, i])) / np.sum(conf_mat[i])

    bal_acc /= len(conf_mat)
    return bal_acc