As discussed earlier, if you have more data, the best choice would be deep networks that perform much better with ample data. Many a time, the more data used, the more accurate the result. The classical ML method needs a complex set of ML algorithms and more data is only going to hamper its accuracy. Complex methods then need to be applied to make up for the less accuracy. Moreover, even learning is affected—it is almost stopped at some point in time when more training data is added to train the model.
This is how this can be depicted graphically:
