Titlebook: Soft Computing for Knowledge Discovery and Data Mining; Oded Maimon,Lior Rokach Book 2008 Springer-Verlag US 2008 Bayesian network.Cluster

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Improved SOM Labeling Methodology for Data Mining Applicationsf SOM to a wider range of potential data mining applications. This work proposes a methodical and semi-automatic SOM labeling procedure that does not require a set of labeled patterns. Instead, nodes in the trained map are clustered and subsets of training patterns associated to each of the clustere

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Data Mining and Agent Technology: a fruitful symbiosision initially, and the improvement, in the long run, of agent reasoning and MAS performance. The coupling of DM and Agent Technology (AT) principles, proposed within the context of this chapter is therefore expected to provide to the reader an efficient gateway for developing and evaluating highly r

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The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining dataset. Although the above situation is of fundamental importance to data mining, it has not been studied from a comprehensive point of view. Thus, this chapter analyzes the above issues in depth. It also proposes a new approach called the HomogeneityBased Algorithm (or HBA) for optimally controll

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d case studies with detailed results...Soft Computing for Knowledge Discovery and Data Mining .is designed for practitioners and researchers in industry. Practitioners and researchers may be particularly intere978-1-4419-4351-4978-0-387-69935-6