gemseo.mlearning.regression.algos.random_forest module#

Random forest regression model.

Use an ensemble of decision trees.

Dependence#

The regression model relies on the RandomForestRegressor class of the scikit-learn library.

class RandomForestRegressor(data, settings_model=None, **settings)[source]#

Random forest regression.

Parameters:

data (Dataset) -- The learning dataset.
settings_model (BaseMLAlgoSettings | None) -- The machine learning algorithm settings as a Pydantic model. If None, use **settings.
**settings (Any) -- The machine learning algorithm settings. These arguments are ignored when settings_model is not None.

Raises:

ValueError -- When both the variable and the group it belongs to have a transformer.

LIBRARY: ClassVar[str] = 'scikit-learn'#: The name of the library of the wrapped machine learning algorithm.

SHORT_ALGO_NAME: ClassVar[str] = 'RF'#

The short name of the machine learning algorithm, often an acronym.

Typically used for composite names, e.g. f"{algo.SHORT_ALGO_NAME}_{dataset.name}" or f"{algo.SHORT_ALGO_NAME}_{discipline.name}".