## S3 method for class 'rpart':
pmml(model, model.name="RPart_Model", app.name="Rattle/PMML",
description="RPart Decision Tree Model", copyright=NULL,
transforms=NULL, dataset=NULL, \dots)
Teradata, for example, generates a single SELECT statement to implement a decision tree. In the Examples section below, we use the rpart example to build a model stored in the variable fit. A segment of the PMML for this model is:
The resulting SQL from Teradata includes:
CREATE TABLE "MyScores" AS ( SELECT "UserID", (CASE WHEN _node = 0 THEN 'absent' WHEN _node = 1 THEN 'absent' WHEN _node = 2 THEN 'absent' WHEN _node = 3 THEN 'present' WHEN _node = 4 THEN 'present' ELSE NULL END) (VARCHAR(8)) AS "Kyphosis" FROM (SELECT "UserID", (CASE WHEN ("Start" >= 8.5) AND ("Start" >= 14.5) THEN 0 WHEN ("Start" >= 8.5) AND ("Start" < 14.5) AND ("Age" < 55) THEN 1 WHEN ("Start" >= 8.5) AND ("Start" < 14.5) AND ("Age" >= 55) AND ("Age" >= 111) THEN 2 WHEN ("Start" >= 8.5) AND ("Start" < 14.5) AND ("Age" >= 55) AND ("Age" < 111) THEN 3 WHEN ("Start" < 8.5) THEN 4 ELSE -1 END) AS _node FROM "MyData" WHERE _node IS NOT NULL) A WHERE "Kyphosis" IS NOT NULL) WITH DATA UNIQUE PRIMARY INDEX ("UserID");
PMML home page:
Zementis' useful PMML convert:
pmml
.library(rpart)
(iris.rpart <- rpart(Species ~ ., data=iris))
pmml(iris.rpart)
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