Support Vector Machines for SQL Server Data Mining

JamieMac — Tue, 14 Oct 2008 20:43:17 GMT

Many have requested that we implement Support Vector Machines (SVM's) for SQL Server 2008, and for a wide variety of reasons, we just couldn't get to it. Luckily the community has come to the rescue for those needing an SVM implementation today! Joris Valkonet of Avanade Netherlands along with colleague Thanh Luc have implemented an SVM plug-in algorithm and viewer. Not only that, but Joris has released the plug-in along with all of the source code at CodePlex so you can customize the algorithm for your own purposes or at least get another example of how algorithms and viewers are implemented.

Below is a screenshot from the viewer showing cancer classification split across two selectable axes with green and blue indicating correctly classified benign and malignant tumors respectively and red indicating misclassifications.

The plug-in and code can be found at http://www.codeplex.com/svmplugin

Visual Numerics integration into SQL Server Data Mining

JamieMac — Fri, 30 May 2008 00:24:18 GMT

Our friends at Visual Numerics, Inc have created an excellent white paper covering the creation of SQL Server Data Mining plug-in algorithms in C#. In addition to documenting all of the architecture and concepts required, they have created a step-by-step tutorial demonstrating how to integrate their own K-Means clustering algorithm into SQL Server Data Mining using the C# interfaces. The entire data mining team here in SQL Server reviewed the paper - we couldn't have done a better job ourselves! Kudos to VNI for such an accomplishment!

The paper includes FULL SOURCE CODE for their plug-in algorithm and is available at http://www.vni.com/company/whitepapers/MicrosoftBIwithNumericalLibraries.pdf. Of course you will need to get a copy of their IMSL C# Numerical Library, for which an eval copy is available upon request to VNI.

As a teaser, here is the TOC for their paper:

Audience ..................................................................................................... 4
Rationale ..................................................................................................... 4
Background ................................................................................................. 5
Plug‐in Architecture .................................................................................... 8
Managed Plug‐in Development .................................................................. 9
IMSL C# Library: ClusterKMeans Integration........................................... 9
Starting up.............................................................................................. 10
Metadata Changes (Metadata.cs) ......................................................... 10
Algorithm Changes (Algorithm.cs) ......................................................... 11
Training and Persistence of patterns..................................................... 11
Persistence of Patterns .......................................................................... 13
Prediction............................................................................................... 13
Algorithm Navigator Changes (AlgorithmNavigator.cs) ........................ 13
Registering the Algorithm with Analysis Services.................................. 14
Debugging .............................................................................................. 15
Other Default Features for Third‐Party Mining Algorithm Developers.... 16
The User Experience ................................................................................. 16
Excel 2007 .............................................................................................. 19
Conclusion................................................................................................. 21
About the Author...................................................................................... 21
References ................................................................................................ 22
Appendix A: Code Files ............................................................................. 23

Jamie's Junk : Plug-ins

Support Vector Machines for SQL Server Data Mining

Visual Numerics integration into SQL Server Data Mining