Lazy vs Eager Learning
Lazy learner:

Just store Data set without learning from it

Start classifying data when it receive Test data

So it takes less time learning and more time classifying data



Eager learner:

When it receive data set it starts classifying (learning)

Then it does not wait for test data to learn

So it takes long time learning and less time classifying data


Hint : In supervised learning

Some examples are :
Lazy : K - Nearest Neighbour, Case - Based Reasoning
Eager : Decision Tree, Naive Bayes, Artificial Neural Networks