def reco_ml_cb_tt(df_test, model_fitted, target='rating', drop_cols=['userId', 'movieId', 'timestamp']):
    """
    Make predictions on the test set and outputs an array of the predicted
    values for them.

    Paramters
    ---------
    df_test      : pandas DataFrame
                   The test set as a transaction table. Each row
                   corresponds to a user's features and that item's features
                   along with the user's rating for that item.

    model_fitted : an sklearn regressor object
                   An object with a fit and predict method that outputs a
                   float. Must be fitted already

    target_col   : str
                   The column corresponding to the rating.
                   
    drop_cols    : list
                   Columns to be dropped in df_test.

    Returns
    -------
    result        : numpy array
                   The results of the model using df_test's features
    """
    df_test = df_test.drop(columns=[target]+drop_cols)
    result = model_fitted.predict(df_test)
    return result