def get_mismatch(model, X_test, y_test, n = 10):
    """analyzes misclassifications of trained machine learning model\n
    | Arguments:
    | :-
    | model (model object): trained machine learning model from train_ml_model
    | X_test (dataframe): motif dataframe used for validating model
    | y_test (list): list of labels
    | n (int): number of returned misclassifications; default:10\n
    | Returns:
    | :-
    | Returns tuples of misclassifications and their predicted probability
    """
    preds = model.predict(X_test)
    preds_proba = model.predict_proba(X_test)
    idx = [k for k in range(len(preds)) if preds[k] != y_test[k]]
    preds = X_test.iloc[idx, :].index.values.tolist()
    preds_proba = [preds_proba[k].tolist()[1] for k in idx]
    mismatch = [tuple([i,j]) for i,j in zip(preds, preds_proba)]
    return mismatch[:min(len(mismatch),n)]