Titlebook: Data Mining and Knowledge Management; Chinese Academy of S Yong Shi,Weixuan Xu,Zhengxin Chen Conference proceedings 2004 Springer-Verlag Be

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https://doi.org/10.1007/978-3-319-59108-7s when data is balanced. The basic data mining algorithms of decision tree, regression-based, and neural network models are considered, using both categorical and continuous data. Two of the data sets have binary outcomes, while the third has a set of four possible outcomes. Key findings are that wh

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https://doi.org/10.1007/978-3-030-05288-1llustrate this, in this article we examine the issue of conduct data mining in mobile computing environments, where multiple physical copies of the same data object in client caches may exist at the same time with the server as the primary owner of all data objects. By demonstrating what can be mine

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Aydın Avkan,Benedek Nagy,Müge Saadetoğluoften than not, important details become saturated and thus, lost amongst the volume of data. With analysis problems ranging from discovering credit card fraud to tracking terrorist activities the phrase “a needle in a haystack” has never been more apt. In order to deal with large data sets current

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Raina Paul,Apurba Sarkar,Arindam Biswasthey study. It would be very helpful to be able to rank the hypothesises using existing data. Microarray technologies enable us to monitor the expression levels of tens of thousands of genes simultaneously. Given the expression levels of almost all of the well-substantiated genes in an organism unde

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https://doi.org/10.1007/978-3-031-23612-9pecially bankruptcy, is measured by a score of aggregate attributes that describe cardholder’s spending history. In the real-life practice, statistics and neural networks are the major players to calculate such a score system for prediction. Recently, various multiple criteria linear programming bas