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Decision Support Using Data Mining. Financial Times Pitman Publishers, London 2. , and Bell, D. 1998. A data mining methodology for cross-sales. Knowledge Based Systems Journal, 10:449–461 3. , and Anand, T. 1996. The process of knowledge discovery in databases: a human-centered approach. , and Uthurusamy, R. ), Advances in Knowledge Discovery and Data Mining 37–58, AAAI Press 4. , and Zanasi, A. 1998. Discovering Data Mining: From Concepts to Implementation, Prentice Hall Saddle River, New Jersey 5.

Communications of the ACM, 44(7), 87–93) 7. Provide a one-page summary of the PMML language standard. Your summary must include information about the newest release of the standard and which data mining models are supported by the standard. Part 2 Data Understanding 3 Data In this Chapter, we discuss attribute and data types, data storage, and problems of quantity and quality of data. 1. Introduction The outcome of data mining and knowledge discovery heavily depends on the quality and quantity of available data.

It consists of a database that stores the data, and a set of programs for management and fast access to the database. The software provides numerous services, such as the ability to define the structure (schema) of the database, to store the data, to access the data in concurrent ways (several users may access the data at the same time) and distributed ways (the data are stored in different locations), and to ensure the security and consistency of the stored data (for instance, to protect against unauthorized access or a system crash).

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