Titlebook: Classification and Clustering for Knowledge Discovery; Saman Halgamuge,Lipo Wang Book 2005 Springer-Verlag Berlin Heidelberg 2005 Extensio

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Recessive Economy and Income Distribution,This paper presents the results of analysis to evaluate the effectiveness of data mining techniques to predict the outcome for missing persons cases. A rulebased system is used to derive augmentations to supplement police officer intuition. Results indicate that rule-based systems can effectively identify variables for prediction.

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The Many Faces of a Kohonen Map A Case Study: SOM-based Clustering for On-Line Fraud Behavior ClassThe Self-Organizing Map (SOM) is an excellent tool for exploratory data analysis. It projects the input space on prototypes of a low-dimensional regular grid which can be efficiently used to visualize and explore the properties of the data.

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Data Mining of Missing Persons Data,This paper presents the results of analysis to evaluate the effectiveness of data mining techniques to predict the outcome for missing persons cases. A rulebased system is used to derive augmentations to supplement police officer intuition. Results indicate that rule-based systems can effectively identify variables for prediction.

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Classification and Clustering for Knowledge Discovery978-3-540-32404-1Series ISSN 1860-949X Series E-ISSN 1860-9503

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https://doi.org/10.1007/b98152Extension; classification; clustering; communication; computational intelligence; data analysis; decision

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978-3-642-06542-2Springer-Verlag Berlin Heidelberg 2005

ECG769

Saman Halgamuge,Lipo WangIncludes supplementary material:

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Studies in Computational Intelligencehttp://image.papertrans.cn/c/image/227194.jpg

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Research Status and Development Trends,g purposes. The methods are the self-organizing map (SOM) and the fuzzy c-means clustering (FCM) algorithm. Application profiles produce significant information about the network’s current state and point out similarities between different applications. This information will be later used to manage

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