def run_model(model, X_train, y_train, X_test, y_test, params):  # pylint: disable=too-many-arguments
    """Train the given model on the training data, and return the score for the model's predictions on the test data.

    Specify parameters of the model with the provided params.

    Args:
        model (callable): model to be initialized with the specified parameters.
        X_train (list-like): features of train set.
        y_train (list-like): labels of train set.
        X_test (list-like): features of test set.
        y_test (list-like): labels of test set.
        params (dict): parameters to specify to the model.
    Returns:
        (float): the accuracy score of the model's predictions on the test set after being trained on the train set.
    """
    clf = model(**params)
    clf.fit(X_train, y_train)
    return clf.score(X_test, y_test)