> ## Documentation Index
> Fetch the complete documentation index at: https://nixtla-old-docs.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> dask LightGBM forecaster

# DaskLGBMForecast

Wrapper of `lightgbm.dask.DaskLGBMRegressor` that adds a `model_`
property that contains the fitted booster and is sent to the workers to
in the forecasting step.

***

<a href="https://github.com/Nixtla/mlforecast/blob/main/mlforecast/distributed/models/dask/lgb.py#L12" target="_blank" style={{ float: "right", fontSize: "smaller" }}>source</a>

### DaskLGBMForecast

> ```text theme={null}
>  DaskLGBMForecast (boosting_type:str='gbdt', num_leaves:int=31,
>                    max_depth:int=-1, learning_rate:float=0.1,
>                    n_estimators:int=100, subsample_for_bin:int=200000, obj
>                    ective:Union[str,Callable[[Optional[numpy.ndarray],nump
>                    y.ndarray],Tuple[numpy.ndarray,numpy.ndarray]],Callable
>                    [[Optional[numpy.ndarray],numpy.ndarray,Optional[numpy.
>                    ndarray]],Tuple[numpy.ndarray,numpy.ndarray]],Callable[
>                    [Optional[numpy.ndarray],numpy.ndarray,Optional[numpy.n
>                    darray],Optional[numpy.ndarray]],Tuple[numpy.ndarray,nu
>                    mpy.ndarray]],NoneType]=None,
>                    class_weight:Union[dict,str,NoneType]=None,
>                    min_split_gain:float=0.0, min_child_weight:float=0.001,
>                    min_child_samples:int=20, subsample:float=1.0,
>                    subsample_freq:int=0, colsample_bytree:float=1.0,
>                    reg_alpha:float=0.0, reg_lambda:float=0.0, random_state
>                    :Union[int,numpy.random.mtrand.RandomState,ForwardRef('
>                    np.random.Generator'),NoneType]=None,
>                    n_jobs:Optional[int]=None, importance_type:str='split',
>                    client:Optional[distributed.client.Client]=None,
>                    **kwargs:Any)
> ```

*Distributed version of lightgbm.LGBMRegressor.*