5.4.5 - Tutorial - Linear Scoring - Teradata Warehouse Miner

Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
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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.

    Linear Regression Reports
    Resulting Scored Table <result_db>.score_linear_1
    Number of Rows in Scored Table 747
    Evaluation
    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