def get_kwargs(clf_name):
    """
    Prepares positional arguments for sklearn model initialisation.

    Parameters
    ----------
    clf_name : string
        The name of the scikit-learn classifer.

    Returns
    -------
    kwargs : Dictionary[string, Union[string, number]]
        A dictionary with named arguments appropriate for the selected model.
    """
    assert isinstance(clf_name, str), 'Classifier name must be a string.'

    if clf_name.endswith('CV'):
        kwargs = dict(cv=5)
    elif clf_name == 'LogisticRegression':
        kwargs = dict(solver='liblinear')
    elif (clf_name.startswith('PassiveAggressive')
          or clf_name in ('Perceptron', 'SGDClassifier', 'SGDRegressor')):
        kwargs = dict(max_iter=40, tol=1e-1, random_state=42)
    # This model is not currently tested.
    # elif clf_name == 'LinearSVR':
    #     kwargs = dict(max_iter=5, tol=1, random_state=42)
    else:
        kwargs = dict()
    return kwargs