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Sklearn Decision Tree

Decision Tree classifier and regressor using scikit-learn

Actions2

Predict

AI-generated

Summary

Predict using a trained scikit‑learn Decision Tree model.

Inputs

  • main (required) — Input items; each must contain numeric values for the columns listed in the 'Feature Columns' parameter.

Output shape

Each input item is returned with an added 'prediction' field. For classifier models a 'probabilities' field is also added. The number of output items equals the number of input items.

No side‑effects other than invoking the Python process to compute predictions.

Examples

Example 1: Classification

Model Type = Classifier, Model Data = , Feature Columns = 'sepalLength,sepalWidth,petalLength,petalWidth' (example), Python Path = python3

Example 2: Regression

Model Type = Regressor, Model Data = , Feature Columns = 'area,bedrooms,age', Python Path = python3

Discussion