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).
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With respect to the achieved speed, the eager classification is faster than lazy classification since the generalization model is built prior of receiving any fresh tuples (i.e. to classify). This thing can also be noticed in case of eager systems; on the other hand, in case of lazy classification, the generalization model for training data is pushed forward until a query is performed in the system....By purchasing this solution you'll be able to access the following files:
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