Sklearn Decision TreeInstall

Summary

Train a scikit‑learn Decision Tree classifier or regressor on the supplied data and return the serialized model together with training metrics.

Inputs

• main (required) — Each input item must contain the columns listed in Feature Columns and the column named in Target Column. Missing values cause the node to fail.

Output shape

single item

The node returns exactly one output item containing the trained model and a set of metadata fields.

Examples

Example 1: Train a classifier on a CSV with features 'age', 'income' and target 'bought'.

Model Type: Classifier; Feature Columns: age,income; Target Column: bought; Max Depth: 5; Random State: 123.