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- Wiley
More About This Title Data Mining with SQL Server 2005
English
Jamie MacLennan is the Development Lead for the Data Mining Engine in SQL Server. He has been designing and implementing data mining functionality in collaboration with Microsoft Research since he joined Microsoft in 1999. In addition to developing the product, he regularly speaks on data mining at conferences worldwide, writes papers and articles about SQL Server Data Mining, and maintains data mining community sites. Prior to joining Microsoft, Jamie worked at Landmark Graphics, Inc. (division of Halliburton) on oil & gas exploration software and at Micrografx, Inc. on flowcharting and presentation graphics software. He studied undergraduate computer science at Cornell University.
English
Credits.
Foreword.
Chapter 1: Introduction to Data Mining.
Chapter 2: OLE DB for Data Mining.
Chapter 3: Using SQL Server Data Mining.
Chapter 4: Microsoft Naïve Bayes.
Chapter 5: Microsoft Decision Trees.
Chapter 6: Microsoft Time Series.
Chapter 7: Microsoft Clustering.
Chapter 8: Microsoft Sequence Clustering.
Chapter 9: Microsoft Association Rules.
Chapter 10: Microsoft Neural Network.
Chapter 11: Mining OLAP Cubes.
Chapter 12: Data Mining with SQL Server Integration Services.
Chapter 13: SQL Server Data Mining Architecture.
Chapter 14: Programming SQL Server Data Mining.
Chapter 15: Implementing a Web Cross-Selling Application.
Chapter 16: Advanced Forecasting Using Microsoft Excel.
Chapter 17: Extending SQL Server Data Mining.
Chapter 18: Conclusion and Additional Resources.
Appendix A: Importing Datasets.
Appendix B: Supported VBA and Excel Functions.
Index.
