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Use a Classification Node to build a Decision Tree (DT) model.
In Oracle Data Mining 12c Release 1(12.1) or later, DT supports nested data.
DT supports text for Oracle Database 12c, but not for earlier releases.
Decision Tree manages its own data preparation internally. It does not require pretreatment of the data. Decision Tree is not affected by Automatic Data Preparation.
Decision Tree interprets missing values as missing at random. The algorithm does not support nested tables and thus does not support sparse data.
By default a Classification Node tests all models that it builds. The test data is created by splitting the input data into build and test subsets. You can also test a DT model using a Test Node. For more information, see Testing Classification Models.
After you build and test a DT model, you can tune it as described in Tuning Classification Models.
To apply a model, use an Apply Node.