By Jamie MacLennan
Know the way to exploit the recent positive aspects of Microsoft SQL Server 2008 for info mining by utilizing the instruments in information Mining with Microsoft SQL Server 2008 , with a view to enable you use the SQL Server facts Mining Toolset with place of work 2007 to mine and learn info. discover all the significant information mining algorithms, together with naive bayes, choice bushes, time sequence, clustering, organization principles, and neural networks. research extra approximately themes like mining OLAP databases, info mining with SQL Server Integration prone 2008, and utilizing Microsoft facts mining to unravel enterprise research difficulties.
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If your HTTP connection requires basic authentication, click the Use a Specific Name and Password button, and enter your user name and password in the corresponding fields (which are also shown in Figure 2-3). After entering all the information in the Connect to Analysis Services dialog box, it is a good idea to use the Test Connection button to ensure that everything works properly. Click OK to close this dialog box, and then close the Analysis Services Connections dialog box as well. You are now ready to use the add-ins.
Tex V2 - 10/04/2008 xxxiv Introduction Chapter 18: Implementing a Web Cross-Selling Application — This chapter walks you through a common data mining scenario — implementing a recommendation engine and integrating it into a retail website. It includes sample queries and code to get you started. Chapter 19: Conclusion and Additional Resources — In addition to wrapping up the book, this chapter provides a list of valuable links where you can find additional information and help with your data mining projects.
Business problems such as churn analysis, risk management, and targeted advertising usually involve classification. Classification is the act of assigning a category to each case. Each case contains a set of attributes, one of which is the class attribute. The task requires finding a model that describes the class attribute as a function of input attributes. In the College Plans data set shown in Figure 1-1, the class is the CollegePlans attribute with two states: Yes and No. A classification model will use the other attributes of a case (the input attributes) to determine patterns about the class (the output attribute).