API methods for training data quantification

The quantity of data should be made visible on the high level interfaces — quantity of data can have multiple aspects to it — (e.g., #recorded Rounds, #examples per round, #total memory consumption). In one instance, one participant noticed the memory of the browser was reaching 3GB, and found this unusual, and also observed the consequences in training time.

Recommendation: Participants would benefit from API methods (namely in the training data class) that provide metrics about quantity or volume of data. This should help developers in design by making them explicit through the visual interface metaphors they develop. It should also be explained in the documentation the consequences of dealing with large data sets (e.g., training time, impact on the classification results outcomes, etc.)