Data mining : know it all by Soumen Chakrabarti, et al

By Soumen Chakrabarti, et al

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Alternatively, you could imagine having individual rules for each of the negative examples, too—an equally uninteresting concept. In either case, the concept description does not perform any generalization; it simply records the original data. On the other hand, if disjunction is not allowed, some possible concepts—sets of examples—may not be able to be represented at all. In that case, a machine learning scheme may simply be unable to achieve good performance. 5 Generalization as Search 31 Another kind of language bias is that obtained from knowledge of the particular domain being used.

The labor negotiations data is from the Collective Bargaining Review, a publication of Labour Canada issued by the Industrial Relations Information Service (BLI 1988), and the soybean problem was first described by Michalski and Chilausky (1980). 7 Resources 35 & Simon 1995); another source of fielded applications is a special issue of the Machine Learning Journal (Kohavi & Provost 1998). The loan company application is described in more detail by Michie (1989), the oil slick detector is from Kubat et al.

Many learning algorithms adopt the former policy, starting with an empty decision tree, or a very general rule, and specializing it to fit the examples. However, it is perfectly possible to work in the other direction. Instance-based methods start with a particular example and see how it can be generalized to cover nearby examples in the same class. Overfitting-Avoidance Bias Overfitting-avoidance bias is often just another kind of search bias. But because it addresses a rather special problem, we treat it separately.

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