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This paper presents a lazy model-based algorithm, named DBPredictor, for on-line classification tasks. The algorithm proposes a local discretization process to avoid the need for a lengthy preprocess stage. Another advantage of this approach is the ability to implement the algorithm with tightly-coupled SQL relational database queries. To test the algorithm’s performance in the presence of continuous attributes an empirical test is reported against both an eager model-based algorithm (C4.5) and a lazy instance-based algorithm (k-NN).
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|Author||Gabor Melli +|
|journal||Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining +|
|title||A Lazy Model-based Algorithm for On-Line Classification +|
|titleUrl||http://www.gabormelli.com/Publications/1999/1999 LazyModelBasedOnlineClassification.pdf +|