gemseo / mlearning / classification

random_forest module

Random forest classification model

The random forest classification model uses averaging methods on an ensemble of decision trees.

Dependence

The classifier relies on the RandomForestClassifier class of the scikit-learn library.

class gemseo.mlearning.classification.random_forest.RandomForestClassifier(data, transformer=None, input_names=None, output_names=None, n_estimators=100, **parameters)[source]

Bases: gemseo.mlearning.classification.classification.MLClassificationAlgo

Random forest classification algorithm.

Constructor.

Parameters

  • data (Dataset) – learning dataset.

  • transformer (dict(str)) – transformation strategy for data groups. If None, do not transform data. Default: None.

  • input_names (list(str)) – names of the input variables.

  • output_names (list(str)) – names of the output variables.

  • n_estimators (int) – number of trees in the forest.

  • parameters – other keyword arguments for sklearn rand. forest.

ABBR = 'RandomForestClassifier'
LIBRARY = 'scikit-learn'