Question

What is eager classification and lazy classification? write their advantages and disadvantages?

Answer 1

Compare the advantages and disadvantages of eager classification (e.g., decision tree, Bayesian, neural network) versus lazy classification (e.g., k-nearest neighbor, case-based reasoning).

Answer 2

In the process of eager classification the generalization of data is made before the query is made just on the basis of the stored training data.

In the process of lazy classification the process of generalization is delayed because the stored training data is inadequate for the generalization of data. Eager classification is prequery generalization process while lazy classification is post query generalization process.

Pros and cons: the process of lazy classification is a delayed process while the eager process is not that much time consuming. On the contrary ,being a pre-query generalization process sometimes undesirable results are obtained.