randomml.ensemble.RVFLBaggingRegressor

class randomml.ensemble.RVFLBaggingRegressor(in_dim, rvfl_kwargs=None, n_estimators=10, random_state=None)

Bagging-based ensemble of RVFLRegressor using sklearn’s BaggingRegressor.

__init__(in_dim, rvfl_kwargs=None, n_estimators=10, random_state=None)

Initializes the Bagging-based RVFLRegressor.

Args:

in_dim (int): Input feature dimension. rvfl_kwargs (dict, optional): Keyword arguments for RVFLRegressor. n_estimators (int): Number of base learners. random_state (int, optional): Random seed for reproducibility.

Methods

__init__(in_dim[, rvfl_kwargs, ...])	Initializes the Bagging-based RVFLRegressor.
fit(X, y)	Fits the Bagging RVFLRegressor.
predict(X)	Predicts using the ensemble model.

fit(X, y)

Fits the Bagging RVFLRegressor.

predict(X)

Predicts using the ensemble model.