1. Eager vs Lazy Classifiers Eager Learning Classification Strategy Classifier builds a full model during an initial training phase, to use later when new query examples arrive. More offline setup work, less work at run-time. Generalise before seeing the query example. Lazy Learning Classification Strategy Classifier keeps all the training examples for later use. Little work is done offline, wait for new query examples. Focus on the local space around the examples.