# Train a tree model

Model / supervised

decision tree, random forest, gradient boosted trees

Page: <https://meridian.online/operations/train-a-tree-model>

## Status

Not built yet.

arcform does not do this yet. [Its place on the roadmap](https://meridian.online/roadmap#train-a-tree-model)

## Variants

- [Train gradient boosted trees](https://meridian.online/operations/train-a-tree-model/train-gradient-boosted-trees): Train trees in sequence, each fitted to the errors of those before it.
- [Train a random forest](https://meridian.online/operations/train-a-tree-model/train-a-random-forest): Train many trees on random samples of rows and columns and average their votes.
- Train a single decision tree: Learn one tree of if-then splits that predicts a class or a number.
- Choose a classification or regression task: Set whether the tree predicts a category or a number.
- Train from code or the command line: Call the training step from an API, a command-line tool or a browser package rather than a visual operator.

## What other tools call it

Meridian's classification; an independent blind rating agreed on 86.2% of 312 rows (exact class, version 2).

- Alteryx Designer: [`Boosted Model`](https://help.alteryx.com/current/en/designer/tools/predictive/boosted-model-tool.html) (read 2026-09-27)
- Alteryx Designer: [`Decision Tree`](https://help.alteryx.com/current/en/designer/tools/predictive/decision-tree-tool.html) (read 2026-09-27)
- Alteryx Designer: [`Forest Model`](https://help.alteryx.com/current/en/designer/tools/predictive/forest-model-tool.html) (read 2026-09-27)
- KNIME Analytics Platform: [`Decision Tree Learner`](https://api.hub.knime.com/nodes/*T2WZJU7jOfyFDtl6?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Gradient Boosted Trees Learner`](https://api.hub.knime.com/nodes/*F6gmERFlrdnszMHb?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Gradient Boosted Trees Learner (Regression)`](https://api.hub.knime.com/nodes/*BNrzDE3e_vcgDY8V?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`KNIME XGBoost Integration (extension)`](https://api.hub.knime.com/extensions/org.knime.features.xgboost) (read 2026-09-27)
- KNIME Analytics Platform: [`Random Forest Learner`](https://api.hub.knime.com/nodes/*2hhbyPN8yXaMD1YU?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Random Forest Learner (Regression)`](https://api.hub.knime.com/nodes/*Ea5mI3GFXonzfQTM?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Simple Regression Tree Learner`](https://api.hub.knime.com/nodes/*yZrYBRw7gRSJnyv6?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Tree Ensemble Learner`](https://api.hub.knime.com/nodes/*hS9r1NhUrO5Ds6UJ?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Tree Ensemble Learner (Regression)`](https://api.hub.knime.com/nodes/*_emYVD9WVlCWiPfz?details=full) (read 2026-09-27)
- mlpack: [`DecisionTree`](https://www.mlpack.org/doc/user/modeling.html) (read 2026-09-27)
- mlpack: [`DecisionTreeRegressor`](https://www.mlpack.org/doc/user/modeling.html) (read 2026-09-27)
- mlpack: [`HoeffdingTree`](https://www.mlpack.org/doc/user/modeling.html) (read 2026-09-27)
- mlpack: [`RandomForest`](https://www.mlpack.org/doc/user/modeling.html) (read 2026-09-27)
- mlpack: [`mlpack_random_forest_train`](https://duckdb.org/community_extensions/extensions/mlpack) (read 2026-09-27)
- RapidMiner Studio: [`CHAID`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/chaid.html) (read 2026-09-27)
- RapidMiner Studio: [`Decision Stump`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/decision_stump.html) (read 2026-09-27)
- RapidMiner Studio: [`Decision Tree`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/parallel_decision_tree.html) (read 2026-09-27)
- RapidMiner Studio: [`Decision Tree (Multiway)`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/decision_tree_multiway.html) (read 2026-09-27)
- RapidMiner Studio: [`Decision Tree (Weight-Based)`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/decision_tree_weight_based.html) (read 2026-09-27)
- RapidMiner Studio: [`Gradient Boosted Trees`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/gradient_boosted_trees.html) (read 2026-09-27)
- RapidMiner Studio: [`ID3`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/id3.html) (read 2026-09-27)
- RapidMiner Studio: [`Random Forest`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/parallel_random_forest.html) (read 2026-09-27)
- RapidMiner Studio: [`Random Tree`](https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/random_tree.html) (read 2026-09-27)
- Talend: [`tDecisionTreeModel`](https://help.qlik.com/talend/en-US/components/8.0/machine-learning/machine-learning-component) (read 2026-09-27)
- Talend: [`tGradientBoostedTreeModel`](https://help.qlik.com/talend/en-US/components/8.0/machine-learning/machine-learning-component) (read 2026-09-27)
- Talend: [`tMatchModel`](https://help.qlik.com/talend/en-US/components/8.0/matching-with-machine-learning/matching-with-machine-learning-component) (read 2026-09-27)
- Talend: [`tRandomForestModel`](https://help.qlik.com/talend/en-US/components/8.0/machine-learning/machine-learning-component) (read 2026-09-27)
- Yggdrasil Decision Forests: [`C++ API: training.h`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/api/training.h) (read 2026-09-27)
- Yggdrasil Decision Forests: [`CART`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/learner/cart/cart.h) (read 2026-09-27)
- Yggdrasil Decision Forests: [`CLASSIFICATION`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/model/abstract_model.proto) (read 2026-09-27)
- Yggdrasil Decision Forests: [`DISTRIBUTED_GRADIENT_BOOSTED_TREES`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/learner/distributed_gradient_boosted_trees/distributed_gradient_boosted_trees.h) (read 2026-09-27)
- Yggdrasil Decision Forests: [`GRADIENT_BOOSTED_TREES`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/learner/gradient_boosted_trees/gradient_boosted_trees.h) (read 2026-09-27)
- Yggdrasil Decision Forests: [`RANDOM_FOREST`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/learner/random_forest/random_forest.h) (read 2026-09-27)
- Yggdrasil Decision Forests: [`REGRESSION`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/model/abstract_model.proto) (read 2026-09-27)
- Yggdrasil Decision Forests: [`train`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/port/python/ydf/learner/generic_learner.py) (read 2026-09-27)
- Yggdrasil Decision Forests: [`train`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/cli/train.cc) (read 2026-09-27)
- Yggdrasil Decision Forests: [`ydf-training (npm)`](https://github.com/google/yggdrasil-decision-forests/blob/0a54b57c95ff0cf42ecf0310ace0513a4f32cb65/yggdrasil_decision_forests/port/javascript/training/npm/README.md) (read 2026-09-27)