randomml.ensemble.RVFLBoostingRegressor

class randomml.ensemble.RVFLBoostingRegressor(in_dim, rvfl_kwargs=None, n_estimators=50, learning_rate=1.0, random_state=None)

Boosting-based ensemble of RVFLRegressor using sklearn’s AdaBoostRegressor.

__init__(in_dim, rvfl_kwargs=None, n_estimators=50, learning_rate=1.0, random_state=None)

Initializes the Boosting-based RVFLRegressor.

Args:

in_dim (int): Input feature dimension. rvfl_kwargs (dict, optional): Keyword arguments for RVFLRegressor. n_estimators (int): Number of boosting iterations. learning_rate (float): Learning rate for boosting. random_state (int, optional): Random seed for reproducibility.

Methods

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

fit(X, y, sample_weight=None)

Fits the Boosting RVFLRegressor.

predict(X)

Predicts using the ensemble model.