Predictions and Results of Data Mining

Predictions and Results of Data Mining

For retrieving information from a processed data mining model, Microsoft® SQL Server™ 2000 Analysis Services supports two different kinds of queries.

Prediction Queries

Prediction queries allow the user to make predictions for unknown case sets using contents from a previously trained data mining model. Prediction queries are run by means of the SELECT statement:

  SELECT [FLATTENED] <SELECT-expressions> FROM <mining model name> 
  PREDICTION JOIN <source data query> ON <join condition>
  [WHERE <WHERE-expression>]

The <Source Data Query> token identifies the set of new cases that will be predicted. <Mining Model Name> identifies the mining model that will be used to generate the predictions.

After the source data has been identified, a relationship between it and the data in the mining model must be defined. This is done using the ON clause of the PREDICTION JOIN statement.

Example

The following example attempts to predict the age of customers using the Age Prediction data mining model and the Customers and Sales cubes:

SELECT t.[Customer ID], [Age Prediction].[Age]
FROM [Age Prediction] 
PREDICTION JOIN 
(
  SHAPE 
  {
  SELECT [Customer ID], [Gender], FROM Customers ORDER BY [Customer ID]
} 
APPEND 
  (
  {SELECT [CustID], [Product Name], [Quantity] FROM Sales ORDER BY [CustID]} 
RELATE [Customer ID] To [CustID]
  ) 
  AS [Product Purchases]
) as t
ON [Age Prediction] .Gender = t.Gender and 
  [Age Prediction] .[Product Purchases].[Product Name] = t.[Product Purchases].[Product Name] and 
  [Age Prediction] .[Product Purchases].[Quantity] = t.[Product Purchases].[Quantity]