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 July 28, 2014  



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Explore filtered models in SQL Server 2008
   Last updated by DMTeam on Mon 04/27/2009 @ 04:45
This articles explores how you can work with filtered models, a powerful new feature introduced in SQL Server 2008 that allows you build models on slices of a mining structure.
 
Under the Hood: How the Naive-Bayes Attribute Discrimination Viewer Gets Its Data
   Last updated by DMTeam on Mon 02/09/2009 @ 11:57
This tip provides insight into how the Attribute Discrimination pane in the Naive-Bayes viewer uses a system stored procedure to get its data
 
Predicting future steps when you do not have enough history
   Last updated by DMTeam on Mon 12/29/2008 @ 06:04
Learn how to use a new SQL Server 2008 feature to get more accurate predictions when you don't have enough historical data for a series.
 
Programmatically generating prediction queries for nested table models
   Last updated by DMTeam on Wed 11/19/2008 @ 12:44
This tip shows you how to take the tedium out of putting together and verifying the correctness of DMX prediction queries for models with multiple nested tables - by generating them programmatically!
 
Getting Data Mining Results Into SQL Tables
   Last updated by DMTeam on Fri 10/24/2008 @ 02:46
Learn how to query mining models from the SQL Server relational database engine using T-SQL and save the results into SQL tables.
 
Explore Time Series enhancements in SQL Server 2008
   Last updated by DMTeam on Fri 08/22/2008 @ 09:33
This article highlights a new downloadable sample that allows you to explore all the new Time Series enhancements in SQL Server 2008.
 
Creating a server data source from DMX
   Last updated by DMTeam on Mon 04/07/2008 @ 07:30
This tip shows you how to create server data sources directly from DMX by calling a stored procedure (that you can build and deploy using the accompanying source code).
 
Try out the new SQL Server 2008 DM Add-ins for Office 2007
   Last updated by DMTeam on Wed 08/06/2008 @ 08:48
This tip shows you how to get all the pieces you need to try out the new SQL Server 2008 DM Add-Ins for Office 2007.
 
How Much Training Data Is Enough?
   Last updated by DMTeam on Tue 01/15/2008 @ 04:31
This tip shows you how you can apply the cross-validation feature in the upcoming SQL Server 2008 release to estimate if the training set size is sufficient for a given model.
 
Under the Hood: How Dependency Probability is Computed by Naïve Bayes
   Last updated by DMTeam on Tue 11/27/2007 @ 10:36
This tip provides insight into the inner workings of the Microsoft Naive Bayes algorithm, showing how the algorithm computes the score used to filter out correlations.
 
Generating accuracy reports using Reporting Services - Part 2
   Last updated by DMTeam on Tue 11/13/2007 @ 01:59

This tip shows you how to apply new DMX syntax to build a False-Positive/False-Negative report using Reporting Services.

 
Programmatically generating HTML visualizations of models using DM Add-ins
   Last updated by DMTeam on Sat 07/28/2007 @ 11:16
This tip shows you how to leverage the programmability component of the Visio DM Add-in to render a model as an interactive web page from your app.
 
Generating accuracy reports using Reporting Services - Part 1
   Last updated by DMTeam on Fri 07/27/2007 @ 08:01
This tip explores a DMX extension introduced in SQL Server 2005 SP2 that can be used to render accuracy reports directly in Reporting Services.
 
Calculating R-Squared for Microsoft regression models
   Last updated by DMTeam on Mon 03/26/2007 @ 11:22
This tip shows you how to compute the R-Squared and Adjusted R-Squared metrics for Microsoft regression models using a stored procedure.
 
Try out the SQL Server 2005 DM Add-Ins for Office 2007
   Last updated by DMTeam on Tue 02/20/2007 @ 04:01
This tip shows you how to get all the pieces you need to try out the new SQL Server 2005 DM Add-Ins for Office 2007.
 
Extracting the regression formula for a regression tree node
   Last updated by DMTeam on Wed 01/24/2007 @ 08:17
This tip explains how to programmatically construct the regression formula on a node from the node distribution content for a regression tree.
 
Extracting Association Rules for specific products
   Last updated by DMTeam on Thu 12/21/2006 @ 10:55
This tip shows you how to extract a set of rules that indicate a certain product from an Association Rules model
 
Stored Procedures to Calculate Covariance and Correlation Matrices
   Last updated by DMTeam on Wed 11/21/2007 @ 11:57
This article describes two stored procedures for the Analysis Server, procedures that compute the Covariance and Correlation matrices
 
Thin Client Viewing with Visio 2007
   Last updated by DMTeam on Mon 11/13/2006 @ 05:45
This sample shows the results of rendering data mining viewers with Visio 2007 and saving as a web page
 
Sampling Nested Tables
   Last updated by DMTeam on Tue 08/29/2006 @ 12:34
This tip shows you how to prepare training and test data sets for mining models with nested tables.
 
Executing predictions from the SQL Server relational engine
   Last updated by DMTeam on Tue 07/18/2006 @ 04:36
This tip shows you how to execute and use the results of prediction queries in multiple ways within the SQL Server relational database engine.
 
Executing multiple DMX statements from SSMS
   Last updated by DMTeam on Tue 06/20/2006 @ 05:06
This article presents a way of executing multiple DMX statements from inside SQL Server Management Studio.
 
Generate DMX creation statements for a server mining structure and contained models
   Last updated by DMTeam on Tue 11/27/2007 @ 06:14
This tip includes code for a stored procedure that generates DMX statements for re-creating an existing server mining structure and its contained mining models.
 
Tracing Mining Model Processing Using AMO
   Last updated by DMTeam on Tue 05/02/2006 @ 05:30
This tip shows how to trace and display the progress of mining model processing with AMO
 
Returning Associative Predictions Based Solely on Rules
   Last updated by DMTeam on Tue 01/22/2008 @ 07:18
This tip shows you how to restrict your associative prediction query results to only those values that are based on rules rather than including popular predictions as well.
 
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