Correct! The amount of training data impacts the accuracy of the system.
Correct! The kinds of answers a QuAM gives depend heavily on the learning algorithm used to build them.
Correct! Features capture signal from the raw data, and are used by the QuAM to perform its task. One function of features can be to filter out irrelevant information.
Correct! Running a QuAM on live data to verify performance against the existing system can be useful.
Correct, some applications may require models to be human-interpretable.
Correct! You should consider what level of accuracy you need for your QuAM to be useful in operation.
Correct! You need to consider how use of the QuAM will change the operating environment.