I have been using the Qboost demo template to solve some binary classification problems. I have a 2 questions:
1) Is there any way to check which items in my test dataset are being classified correctly and which aren't? It merely gives me a percent accuracy, I've been unsuccessful at my attempts to extract any lower-level data.
2) Is there any way to "save" the model that is created by the training dataset in order to readily classify future items that aren't currently in my testing dataset? That is, do I need to feed in the same training data every time I want to re-run the machine learning algorithm to classify a new point?