I have recently started using the time series models in data robot for monthly data of mine. I was able to train this data and get a model. However, when forecasting for future values, it is only doing so for 3 months into the future. How can I change this forecast distance/forecast window to encompass a larger range of months. Note I use python to communicate with the data robot api so an answer in python would be great. Thanks.
Here is the code
If you have a calendar that you want to use you can upload it to DataRobot this way
calendar = dr.CalendarFile.create('Acme_Calendar.csv', calendar_name = 'US_Calendar')
def start_modeling(projectName,data_df): '''provide a project name, and the dataframe for training 1. Create project 2. Set specifications for time-series modeling 3. Start project''' project = dr.Project.create(project_name=projectName, sourcedata=data_df) mySpec = dr.DatetimePartitioningSpecification( datetime_partition_column=ts_settings['date_col'], use_time_series=True, multiseries_id_columns=[ts_settings['series_id']], default_to_known_in_advance=False, feature_derivation_window_start=ts_settings['fdw_start'], feature_derivation_window_end= ts_settings['fdw_end'], forecast_window_start=ts_settings['fd_start'], forecast_window_end=ts_settings['fd_end'], calendar_id=calendar.id ) project.set_target( target = ts_settings['target'], partitioning_method = mySpec, mode=dr.AUTOPILOT_MODE.FULL_AUTO ##### Here is where we can change to dr.AUTOPILOT_MODE.FULL_AUTO ) project.wait_for_autopilot() ##Wait for autopilot to finish return(project) #Create and Start Project project = start_modeling(ts_settings['project_name'],ts_settings['use_time_series'])
Also, you can find a full python solution for time-series in here
I think you could change the input values when you start configuration for Forecast Window,then go to Advanced Options -> Configure Backtesting to check forecasting future period.