# Tutorial - Linear Scoring - Teradata Warehouse Miner

## Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
dita:mapPath
yuy1504291362546.ditamap
dita:ditavalPath
ft:empty
dita:id
B035-2302
Product Category
Software

In this example, the same table is scored as was used to build the linear model, as a matter of convenience. Typically, this would not be done unless the contents of the table changed since the model was built. In the case of this example, the Standard Error of Estimate can be seen to be exactly the same, 10.445, that it was when the model was built (see Tutorial - Linear Regression).

1. Parameterize a Linear Regression Scoring analysis as follows:
• Selected Table — twm_customer_analysis
• Evaluate and Score — Enabled
• Use dependent variable for predicted value column name — Enabled
• Residual column name — Residual
• Result Table Name — twm_score_linear_1
• Index Columns — cust_id

2. Run the analysis.
3. Click Results when it completes.

For this example, the Linear Regression Scoring/Evaluation analysis generated the following pages. A single click on each page name populates Results with the item.

 Resulting Scored Table .score_linear_1 Number of Rows in Scored Table 747
 Minimum Absolute Error 0.0056 Maximum Absolute Error 65.7775 Average Absolute Error 7.2201 Standard Error of Estimate 10.4451
Data
cust_id cc_rev Residual
1362480 59.188 15.812
1362481 3.412 -3.412
1362484 12.254 -.254
1362485 28.272 1.728
1362486 -9.026E-02 9.026E-02
1362487 14.325 -1.325
1362488 -5.105 5.105
1362489 69.738 12.262
1362492 53.368 .632
1362496 -5.876 5.876