Classification models options

KNNClassifier

class gemseo.mlearning.classification.knn.KNNClassifier(data, transformer=None, input_names=None, output_names=None, n_neighbors=5, **parameters)

K nearest neighbors 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_neighbors – number of neighbors.

• parameters – other keyword arguments for sklearn KNN.

RandomForestClassifier

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

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.