June 2011
Beginner to intermediate
744 pages
25h 11m
English
The classification methods discussed so far in this book—decision tree induction, Bayesian classification, rule-based classification, classification by backpropagation, support vector machines, and classification based on association rule mining—are all examples of eager learners. Eager learners, when given a set of training tuples, will construct a generalization (i.e., classification) model before receiving new (e.g., test) tuples to classify. We can think of the learned model as being ready and eager to classify previously unseen tuples.
Imagine a contrasting lazy approach, in which the learner instead waits until the last minute before doing any model construction to classify a given test ...
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