How to run Skforecast with Auto-Sklearn 2.0 regressor
I want to run AutoML time series forecasting with Auto-Sklearn 2.0 (https://www.automl.org/auto-sklearn-2-0-the-next-generation/), which natively only supports classification and regression, so I have to turn the time series forecasting task into a regression task and use Auto-Sklearn’s regressor method for recursive regression.
I want to use OpenSource software for this, and propose Skforecast (https://cienciadedatos.net/documentos/py27-time-series-forecasting-python-scikitlearn.html). Concretely I will use Skforecast’s recursive forecast using Auto-Sklearn’s autosklearn.regression class’s AutoSklearnRegressor() method. I.e. I will as in the below example from https://cienciadedatos.net/documentos/py29-forecasting-electricity-power-demand-python replace the LGBMRegressor with autosklearn.regression class’s AutoSklearnRegressor() method.
How to run Skforecast with Auto-Sklearn 2.0 regressor
I want to run AutoML time series forecasting with Auto-Sklearn 2.0 (https://www.automl.org/auto-sklearn-2-0-the-next-generation/), which natively only supports classification and regression, so I have to turn the time series forecasting task into a regression task and use Auto-Sklearn’s regressor method for recursive regression.
I want to use OpenSource software for this, and propose Skforecast (https://cienciadedatos.net/documentos/py27-time-series-forecasting-python-scikitlearn.html). Concretely I will use Skforecast’s recursive forecast using Auto-Sklearn’s autosklearn.regression class’s AutoSklearnRegressor() method. I.e. I will as in the below example from https://cienciadedatos.net/documentos/py29-forecasting-electricity-power-demand-python replace the LGBMRegressor with autosklearn.regression class’s AutoSklearnRegressor() method.
How to run Skforecast with Auto-Sklearn 2.0 regressor
I want to run AutoML time series forecasting with Auto-Sklearn 2.0 (https://www.automl.org/auto-sklearn-2-0-the-next-generation/), which natively only supports classification and regression, so I have to turn the time series forecasting task into a regression task and use Auto-Sklearn’s regressor method for recursive regression.
I want to use OpenSource software for this, and propose Skforecast (https://cienciadedatos.net/documentos/py27-time-series-forecasting-python-scikitlearn.html). Concretely I will use Skforecast’s recursive forecast using Auto-Sklearn’s autosklearn.regression class’s AutoSklearnRegressor() method. I.e. I will as in the below example from https://cienciadedatos.net/documentos/py29-forecasting-electricity-power-demand-python replace the LGBMRegressor with autosklearn.regression class’s AutoSklearnRegressor() method.
How to run Skforecast with Auto-Sklearn 2.0 regressor
I want to run AutoML time series forecasting with Auto-Sklearn 2.0 (https://www.automl.org/auto-sklearn-2-0-the-next-generation/), which natively only supports classification and regression, so I have to turn the time series forecasting task into a regression task and use Auto-Sklearn’s regressor method for recursive regression.
I want to use OpenSource software for this, and propose Skforecast (https://cienciadedatos.net/documentos/py27-time-series-forecasting-python-scikitlearn.html). Concretely I will use Skforecast’s recursive forecast using Auto-Sklearn’s autosklearn.regression class’s AutoSklearnRegressor() method. I.e. I will as in the below example from https://cienciadedatos.net/documentos/py29-forecasting-electricity-power-demand-python replace the LGBMRegressor with autosklearn.regression class’s AutoSklearnRegressor() method.