1.1 - 8.10 - DecisionForest Example: TreeType ('classification'), OutOfBag ('true') - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

Like DecisionForest Example: TreeType ('classification'), OutOfBag ('false'), this example uses home sales data to create a classification tree that predicts home style, which can be input to the DecisionForestPredict_MLE Example: Omit Responses. However, this example outputs the out-of-bag error.

SQL Call

SELECT * FROM DecisionForest (
  ON housing_train AS InputTable
  OUT TABLE OutputTable (rft_model_oob)
  OUT TABLE OutputMessageTable (housing_monitor_table)
  USING
  ResponseColumn ('homestyle')
  NumericInputs ('price','lotsize','bedrooms','bathrms','stories','garagepl')
  CategoricalInputs
   ('driveway','recroom','fullbase','gashw','airco','prefarea')
  TreeType ('classification')
  MinNodeSize ('2')
  MaxDepth ('12') 
  NumTrees ('50')
  Mtry ('3')
  OutOfBag ('true') 
) AS dt;

Output

 message                                          
 ------------------------------------------------ 
 Computing 50 classification trees.              
 Each worker is computing 25 trees.              
 Each tree will contain approximately 246 points.
 Poisson sampling parameter: 1.00                
 OOB estimate of error rate: 3.462321792260693%  
 Decision forest created.

The model table, rft_model_oob, looks the same as it does in DecisionForest Example: TreeType ('classification'), OutOfBag ('false').

Download a zip file of all examples and a SQL script file that creates their input tables from the attachment in the left sidebar.