XGBoostRegressor

XGBoostRegressor

A model type for constructing a eXtreme Gradient Boosting Regressor, based on XGBoost.jl, and implementing the MLJ model interface.

From MLJ, the type can be imported using

XGBoostRegressor = @load XGBoostRegressor pkg=XGBoost

Do model = XGBoostRegressor() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in XGBoostRegressor(test=...).

Univariate continuous regression using xgboost.

Training data

In MLJ or MLJBase, bind an instance model to data with

m = machine(model, X, y)

where

• X: any table of input features whose columns have Continuous element scitype; check column scitypes with schema(X).
• y: is an AbstractVector target with Continuous elements; check the scitype with scitype(y).

Train using fit!(m, rows=...).

Hyper-parameters

See https://xgboost.readthedocs.io/en/stable/parameter.html.